First Monday

I second that emoji: The standards, structures, and social production of emoji by Bethany Berard

How does an emoji come to be? In 2010 emoji character sets were incorporated into Unicode Standard 6 which allowed “picture characters” to become standardized alongside text-based characters. The technical standardization allowed emoji to be used across devices, operating systems, and Internet platforms, producing a technical codification that made it easier for emoji to circulate widely. This paper provides a brief history of emoji, focusing on the technical standardization that demarcates emoji as unique from emoticons or other pictographic or iconographic formats, and examines the factors Unicode delineates as key for emoji inclusion and exclusion, and who ultimately decides whether an emoji will be created.


Unicode: Standard setting at a cost
Emoji: What exactly are we looking at?
From conception to codification: Creating an emoji
Social uses of technical standards or the social production of technical standards?
Emoji: Making standards visible with a 😄




Companies use them (Ember, 2015; Goel, 2015). Marketers want them (Darlin, 2015; Holf, 2016; Tugend, 2015). Politicians and diplomats get in trouble for misusing them (Knott, 2015, Ramzy, 2015). Judges have read them into official court transcripts, and they have been used to convict individuals of harassment (Kirley and McMahon, 2017; Weiser, 2015; Zavadski, 2015). Emoji, pictographs with a distinct cartoonish aesthetic, are having a moment. In November 2015 the Oxford English Dictionary chose 😂 as the word of the year. This decision sparked debate about the nature of emoji: Are they words, pictures, pictographs, ideographs? Some, like linguist Vyyan Evans (2015), have wondered if emoji constitute a new language. This is an interesting line of inquiry, but the prevalence of emoji in contemporary culture also shows that they need to be examined together with their spheres and methods of use, as this special issue aptly demonstrates. As the aforementioned examples illustrate, emoji are not simply an example of what Jonah Bromwich (2015) calls “mobile pop culture” as there are material commercial, political, and legal consequences of their use (Kirley and McMahon, 2017). But how do emoji come to be? Who decides which emoji are made, and what is the process? The analysis that follows answers these questions by examining the Unicode Consortium (the organization responsible for emoji standardization), and the process and procedures Unicode follows when considering the submission of new emoji. This paper utilizes a multi-directional, social constructivist approach “to ask why some [technological] variants ‘die’ and others ‘survive’” [1]. Emoji are an example of a particular variant of picture or image-based graphics that survived, in part, because of an intentional process of technical standardization. The technical standardization of emoji through the Unicode Consortium is arguably a “constitutive moment” as after this standardization emoji are accessible across devices, operating systems and platforms. A component of the increase in popularity and widespread use of emoji can be attributed to their cross-platform, cross-device compatibility. As a result of their incorporation into the Unicode Standard, the continued growth and production of new emoji are authorized by the Unicode Consortium [2]. This is important to note, because those shaping and codifying this specific component of online visual language are able to do so because of paid membership as part of the Unicode Consortium. Kyongsok Kim (1992) examined practices of character standardization in the early phases of Unicode and observed that within the technical codification or systemization of characters there are political consequences as particular marginalized groups’ linguistic characters may not show up. Kim’s work asks who decides what gets to count within the standard, and are there commercial interests at play in these decisions of standardization? Emoji are not linguistic characters per se, but similar questions have been asked of them. Who is represented in emoji and why? Racial diversity, gender equality, and LGBTQ* representation have all become part of the discussion about what is included in the emoji cannon, and the gaps in visual representation that need to be addressed. Questions of representation extend to the choice of icons and symbols chosen for inclusion, and one can ask if certain ways of seeing the world are reproduced as a result of the current model of the Unicode Consortium where a specific set of corporate, institutional, and governmental actors decide which emoji will become visible.

To address these questions this paper aligns with the tradition of political economy of communication which “focuses on the actors, interests, and institutions that maintain structures over time or, alternatively, coalesce to challenge them in favor of new ‘rules of the game’” [3]. Political economy of communication focuses on how power manifests in these constitutive moments where specific arrangements of communication technologies are cemented. Examining the structure of Unicode provides insight into the institutions and individuals that ‘pay-to-play’ and are therefore responsible for the technical standardization of emoji. As Jeffrey Nickerson and Michael zur Muehlen note, “Researchers shut out commercial interests while the initial Internet standards were born. At this point, however, commerce depends on the Internet, so companies strive for control,” [4] and as such, it is important to consider who controls the standards of emergent Internet culture and technology, of which emoji are a contemporary and important example of digital visual communication. Whether political and/or commercial interests prevail, emoji are an example of control of communicative elements, which limit and shape how and what can be said in this particular digital visual form. Thus while seemingly innocuous, the deliberative process that leads to which emoji are made is a significant site of cultural power, as those who set the factors for inclusion and exclusion, and those who vote on individual proposals, are responsible for setting part of the contemporary digital visual lexicon.



Unicode: Standard setting at a cost

Unicode is a computing industry standard that systematizes character coding to ensure consistent encoding, text display, processing, and interchange over different platforms by designating a specific number to each alphanumeric and emoji character that any computer will recognize (Bromwich, 2015; see also Kim, 1992; Liu and Lions, 1998). Unicode is defined as “the foundation for text in all modern software: it’s how all mobile phones, desktops, and other computers represent the text of every language” [5]. During the late 1980s different computers used different codes for the same letter, and had difficulty talking to one another [6]. At the time, character coding was primarily set by ASCII, the American Standard Code for Information Exchange, a Latin-based script. ASCII operated alongside numerous extensions for non-Latin based scripts, and as a result ASCII and its extensions were used in many countries. ASCII extensions, however, were comprised of national standards which often conflicted with one another making the “design of multilingual information systems complicated” [7]. A character set that could be shared by all countries and operating systems thus quickly became imperative to the development of global digital information processing in the early 2000s, and Unicode Standard was one answer to this problem, since the Consortium had begun working on a coding procedure that would unify conflicting ASCII extensions into one coding architecture in the early 1990s (Crystal, 2006; Liu and Lions, 1998; Needleman, 2000; Unicode Consortium, 2018h; Wu, 2000). Unicode Standard has quickly developed into an industry standard. In 2010 Google reported 50 percent of Web pages were encoded in Unicode, and in 2013 over 70 percent of the 10 000 most visited sites used Unicode. Unicode is now built into XML, Extensible Markup Language, which defines the rule set for encoding documents. XML “lies at the foundation of Microsoft Office and Apple’s iWork software,” [8] and as such Unicode Standard is indispensable to much of modern day office software.

Unicode’s character standard is developed and organized through the Unicode Consortium (Unicode Inc.), a membership based non-profit organization. Membership in the Consortium is available to companies, institutions, non-profit groups, or individuals, and membership levels come at various price points (see Figure 1).


Unicode membership levels


However, not all membership levels are created equal. Though all members can participate in the Technical Committee meetings, where the discussions about the introduction of new character proposals and refinement or changes to existing character codes (amongst other things) take place, only full and institutional members votes carry the weight of a full vote, while supporting members votes carry half the weight (Unicode Consortium, 2018i). All other membership categories, while able to voice an opinion, do not have a weighted vote (see the Appendix for a detailed comparison of membership levels and their perks). Further, Unicode rewards sustained engagement by offering membership discounts for multi-year memberships with three-year membership at a six percent discount, five-year at a 10 percent discount, and those that commit to a ten-year membership receive a 20 percent discount on their membership fee (Unicode Consortium, 2018c). The Unicode Consortium is transparent about its membership and membership history [9]. Full, institutional, supporting, and associate members receive a marquee listing on Unicode’s homepage, as well as a link to their Web site, and individual and student members are listed by name on the Unicode membership page. Unicode also makes its membership history available on their Web site dating back to 1991 when the first iteration of Unicode Standard was published [10].

The makeup of Unicode’s full voting membership is primarily North American technology companies. For example, in 2015, Adobe, Apple, Facebook, Google, Hewlett-Packard, IBM, Microsoft, Monotype Imaging, Oracle, and Yahoo all were full-paid voting members. A notable exception is the Chinese ICT company Huawei which joined Unicode as a full voting member in 2015. Many of the Unicode Consortium’s executive officers and board of directors are currently employed by, or have been employed by, the aforementioned tech companies. As a result, the Consortium has an official conflict of interest policy which “protect[s] the interest of Unicode, Inc. (‘Unicode’) when it is contemplating entering into a transaction or arrangement that might benefit the private interest of an officer or director of Unicode or might result in a possible excess benefit transaction” [11].

The number of associate members has grown significantly since 2010, which includes a variety of non-profit organizations such as Emojination, EmojiOne, EmojiXPress, the Perl Foundation, and OCLC, as well as for-profit corporations like Sony Pictures Animation, Tinder, and Twitter, as of 2018 (Unicode Consortium, 2018k). However, associate members cannot vote on character proposals, despite their growth in numbers and the increasingly public profile of the Consortium.

Emoji have become a central component to the increased publicity of the Unicode Consortium, and while the growing popularity of emoji has not changed how Unicode operates, groups like EmojiOne [12] and EmojiXpress [13] being associate or full members since 2015 indicates that there are groups dedicated to developing the emoji-specific components of the Unicode Standard. This increased visibility of the Consortium and its practices is to some degree a result of emoji, as Unicode Consortium co-founder and president Mark Davis stated in an interview in Time “As far as Unicode goes, it’s something that, if we do our jobs right and text just works on the screen, then we are fairly invisible. It’s only really emoji that have brought us to the public knowledge” [14].



Emoji: What exactly are we looking at?

One of the challenges of researching emoji is the relatively ambiguous nature of the term “emoji” in everyday conversation. Here, “emoji” references a particular set of 12 x 12 pixel images that are displayed on digital devices and platforms as a single character of in-line text, through the Unicode Standard character code. Emoji are technically defined by Unicode as a “standardized set of characters” that are available on multiple platforms and operating systems including iOS, Android, Windows and Mac OS X (Davis and Edberg, 2015). Though different operating systems or platforms may render a slightly different aesthetic for each character, the character’s integrity is maintained as each character has a unique numerical code, and is given an official name that ensures characters appear similar across platforms and devices (Unicode Consortium, 2018f). This technical standardization allows emoji to be used and recognized across devices, operating systems, and Internet platforms. The ability to transcend devices or platforms is crucial to increased circulation and use, as the successes or failures of brands, devices, or platforms does not affect emoji or their continued availability. I argue standardization not only facilitates circulation and increases the potential of rapid and widespread adoption, but demonstrates a particular form of control over technology (Abbate, 1999) that thus necessitates a discussion of who is setting these standards, and at what cost, particularly because Unicode has a strict character stability policy, so “once a character is encoded, it will not be moved or removed” [15] nor will the character name be changed. This policy adds another layer to the questions of control as the decisions made by those involved in Unicode have a potentially permanent effect on character availability and display on the Internet.

Emoji originated in Japan in the late 1990s. Broadly inspired by manga, Chinese characters, and street signs, emoji were proposed as “a better way to incorporate images in the limited visual space available on cell phone screens” [16]. Developed by technical designer Shigetaka Kurita for the Japanese mobile company NNT DoCOMO’s I-mode mobile internet, 176 12 x 12 pixel images were released in 1999 and would become the foundation of what are now referred to as emoji (Galloway, 2016; Negishi, 2014). The name “emoji” comes from the Japanese characters for picture, (絵 = e) and letter or written character (文字 = moji) which encompasses the pictographic style of emoji [17]. In English, “emoji” is often assumed to be a reference to “emotion,” as the popular text based “emoticons” (“emotion” + “icon”) or the use of punctuation symbols to make emotive faces e.g., :-) are both used to convey emotive elements in digitally-mediated communication. From inception, however, emoji were a wide range of pictorial and representative symbols that encompassed more than emotive characters or images, and this is another way emoji are distinct from earlier digital textual elements that indicate emotion. Much scholarship has focused solely on the emotive elements of pictorial or non-linguistic text, such as the way emotive components of computer mediated communication operate in electronic social communication, primarily focused on teens and young adults, (Baron and Ying, 2011; Derks, et al., 2008; Garrison, et al., 2011; Haas, et al., 2011; Miyake, 2007), on the role of emotive components in electronic business communication (Skovholt, et al., 2014), as well as on where emotive characters appear on the Internet (Derks, et al., 2007). While research on emoji exclusively has yet to be sufficiently developed, Marcel Danesi’s (2016) The semiotics of emoji, and Luke Stark and Kate Crawford’s (2015) “The conservatism of emoji: Work, affect, and communication” are notable examples of specific work on emoji, which attend to more than just the emotive elements that emoji visually represent, drawing attention to the communicative and semiotic potential of emoji.

By 2009, there were 722 emoji characters available to Japanese mobile users. 114 of these Japanese emoji characters were coded into Unicode 5.2 in 2009, which meant that operating systems using Unicode could render these pictorial characters in-text just like any other standardized character. The 114 emoji in Unicode 5.2 were primarily characters taken from the Japanese ARIB: Association of Radio Industries and Business broadcasting symbol set and were presented at a Unicode Technical Committee meeting in 2007 by Michel Suignard, a Unicode character editor, as a specific character set for inclusion. The rationale provided was that while much of Japanese text had been incorporated into earlier versions of Unicode, there were many other symbols that were used in textual communication which had led to the creation of “Private Use characters” which Suignard argued could cause confusion for end users [18]. In a move to further standardize pictorial text, once these 114 characters were incorporated into the Unicode Standard in 2009, Unicode defined them as “explicitly intended as emoji” [19] and began to demarcate pictorial text as distinct from letters or characters within the Unicode Standard.

On Friday, 6 February 2009 the Unicode Technical Committee voted to include 674 emoji characters in a future version of Unicode Standard, and this is the first time the term “emoji” is documented in UTC meeting notes (Unicode Consortium, 2009). The motion was moved by Unicode co-founder and President Mark Davis, seconded by Peter Edberg, a senior software engineer at Apple. Representatives from Adobe, Apple, Google, IBM, Microsoft, Sun Microsystems Inc., Sybase Inc., University of California at Berkeley, and Yahoo voted in favour of the motion, and NetApp (a hybrid cloud data service company) voted against it, so the motion was carried nine to one. The majority of potential Unicode voting members at this time were primarily North American technology corporations, and thus the choice to designate “emoji” as a specific subset of text-based characters for standardization was a result of input from primarily corporate entities.

The approved 674 emoji characters were added to Unicode Standard 6 in 2010 and since then new emoji have been coded into each subsequent version of the Unicode Standard. Emoji are updated on an ongoing basis and the Unicode Consortium has projected an average addition of 60 new emoji per year. As of Unicode 11 there are 2,530 distinct emoji characters [20], which include a multitude of pictorial characters inclusive of icons that indicate emotions, activities, objects, human figures, weather, vehicles and buildings, food and drink, animals and plants, flags, and other communicative symbols. Several characters have multiple variations, for example, emoji activities often have a male and female emoji for that activity, and emoji people can be displayed with variation in skin colour based on the six tones of the standardized Fitzpatrick scale. With these variations there are approximately 2,789 emoji possible in Unicode Standard 11, which are supported by current operating systems and platforms [21].

Each emoji is designated a specific technical code point and is also given an official name. For example, 😂’s code point in Unicode Standard is U+1F602, and it’s CLDR short name [22] is “Face with Tears of Joy.” Emoji are thus “codified” in both a technical and social sense as both the technical code point of the character is standardized, while the designation of an official name codifies a dominant or traditional reading and an implied correct usage. This does not, however, mean that emoji are used in a mono-semantic way. Though emoji are given official names which imply a particular meaning for that emoji, just as language is polysemic, so are emoji. To this end the Unicode chart that lists each emoji’s unique identifier includes annotations of other possible keywords or meanings for the given emoji. How emoji are used by different social groups can also create additional and alternative meanings to those listed by Unicode.

Although there is a standardized code for each emoji, the same characters have a different aesthetic across different devices, platforms, and vendors. This is made clear in Unicode’s official “Full Emoji List” where they document the variety of renderings possible for each emoji, alongside the official number, code and CLDR short name (Unicode Consortium, 2018g). As Figure 2 demonstrates, these aesthetic differences can be negligible, as in the example of the “#1: grinning face,” or more substantial as in the cases of “#286 woman golfing” or “#447 necktie” where colors and positioning or angles of presentation are notably different.


Examples of emoji rendering across various devices/applications/vendors
Figure 2: Examples of emoji rendering across various devices/applications/vendors (Unicode, 2018f).
Note: Larger version of figure available here.




From conception to codification: Creating an emoji

With the exception of the original 722 emoji created in Japan, all new emoji are proposed to the Unicode Consortium for consideration. Following the correct procedure, any individual, association, organization, or institution can submit a proposal for a new Unicode Standard character to the Unicode Consortium [23], which can include the proposal of traditional linguistic text based characters, or pictographs. The first step in proposing a new emoji is a 53–question form that must be submitted alongside the emoji name and keywords, and what Unicode terms “frequency of use” which requires proposals to present evidence that the proposed emoji character is going to be widely used (Unicode Consortium, 2018j, 2016). A set of images for the proposed character, as well as a suggestion of where the character would be placed in the Emoji Ordering [24] are also required components of a complete proposal. For example, Maximilian Merz, a German university student with no previous affiliation to Unicode, successfully proposed “Face With One Eyebrow Raised” character in late 2015 (included in the Unicode Standard 10 update in 2017). Mertz spent a week on the proposal, which was 2,700 words long and included a link to a Reddit thread where there were “hundreds of other people asking for the same emoji.” Further, “Merz meticulously described how 18 other emoji showing varying degrees of perturbation (Smirking Face, Worried Face, Anguished Face) cannot convey the same why-am-I-not-surprised surprise Face With One Eyebrow Raised can” [25].

Proposals for a new emoji are submitted to the Emoji Subcommittee, a subcommittee of Unicode’s Technical Committee, and are assessed against a list of factors for inclusion or exclusion. Factors for inclusion involve the following: compatibility, which assess whether the emoji is needed for compatibility with icons or pictographs frequently used in other popular systems. Expected usage level, which determines if there is evidence to suggest 1) high frequency of use, 2) the potential for multiple uses (including metaphorical references or symbolism), 3) its potential to be used in sequences and 4) the potential to represent something new and different [26]. Image distinctiveness measures whether the image or object depicted is easily recognizable and easily distinguished from existing emoji. Completeness determines whether the proposed character fills a gap in the existing types and variations of emoji. Finally, the frequency of requests for a particular emoji is a key factor in evaluation for inclusion. While commercial petitions for specific emoji do not guarantee the success of an emoji proposal, the Consortium is keen on public feedback about proposed emoji, and thus the social momentum commercial petitions can achieve, largely through social media avenues, may have a positive impact on the overall proposal, though commercial petitions for the creation of specific emoji are cited as not having a large role in emoji selection (Unicode Consortium, 2018j, 2016).

Evidence of expected usage must also be included in the proposal of a new emoji, which has produced a growing tradition of non-commercial petitioning of Unicode to create particular emoji, or emoji sets. For example, Signily, a keyboard application designed by ASLized (a non-profit organization that produces educational videos in American Sign Language) that includes American Sign Language hand signs, has petitioned Unicode to make ASL officially part of the standardized emoji offerings [27]. For-profit companies have made similar moves in petitioning for a generic emoji that represents their product, like the condom manufacturer Durex who has called on Unicode to produce a safe-sex emoji (see Figure 3).


Durex petition for a #CondomEmoji on Facebook
Figure 3: Durex petition for a #CondomEmoji on Facebook (Durex Canada, 2015).


In 2015, the fast-food chain Taco Bell petitioned for a taco emoji collecting 25,000 signatures in three months from a petition [28]. Despite the Consortium’s claim that commercial petitions do not influence the creation of new emoji, a taco emoji was released later the same year (Hof, 2016).

The list of factors for inclusion are not the only standards by which emoji proposals are measured, as the Consortium outlines elements that would cause a proposal to be excluded from consideration. Factors for exclusion include if the emoji is overly specific, or if it is too open ended, or, if the emoji is one of something of which there are a multitude of other options (e.g., a specific profession). A proposal could be excluded if the proposed emoji is deemed already representable, meaning that the proposed character can already be represented by an existing emoji or a sequence of existing emoji. Proposals of characters that look like logos, brands, signage, specific people, buildings or deities would also be denied. Finally, proposals that are too similar to an existing, compatible emoji (faulty comparison); transient (if proposed emoji content is determined to be just a fad and judged not have projected long term use) or an exact image, where proposal requests an exact or “precise image” from a meme or similar Internet content would all be excluded from consideration. Unicode notes, however, that alongside these general factors for inclusion and exclusion, “other considerations are taken into account” at the Unicode Technical Committee quarterly week-long meetings. The Consortium has also noted that compatibility and expected usage level are the most important factors when assessing emoji for inclusion (Unicode Consortium, 2018j, 2016) [29].

The aforementioned criteria for inclusion/exclusion exemplify the social nature of the process of emoji creation not only because some of the criteria for inclusion are oriented around how the emoji might be used in terms of potential popularity and the probability of different uses, but also in the social nature of how these proposals can come from both individuals and groups, and are assessed by a committee. Emoji are an example of the social construction of technology insofar as there is an explicit statement of the requirement of interpretive flexibility of individual emoji, thus making it more likely to be produced. In social constructivist approaches to the study of technology “the interpretative flexibility of a technological artifact must be shown,” [30] as well as considering how social groups compete for control of the technological design. Social constructivist approaches to technology also recognize that relevant social groups might contribute different interpretations or uses of a technology, and there are particular social groups involved in the history of emoji development. Hence, to examine the evolution of emoji is to consider the social nature of the way technology is used and consider that as a primary method of evaluation of a proposals success. In stating expected usage levels as an important factor for inclusion alongside criteria like frequency of requests users and their particular needs and wants becomes integral to the production and subsequent evaluation of new emoji.

Once an emoji proposal has been approved by the Emoji Subcommittee it is then presented to the Unicode Technical Committee which makes the final decision about all new Unicode standard character inclusions. As cited above, all Unicode members, regardless of their membership level, may participate in the Technical Committee meetings, but only full, institutional, and supporting members votes carry any weight in the final decisions (see the Appendix). Thus, while there can be robust representation in discussion about the proposed emoji, the final decision about which emoji proposals will be accepted is made by those who can afford the higher, more expensive, membership tiers which are primarily populated by large, North American technology corporations. If a proposed character is approved, the technical code point for that character is included in the next Unicode update. Unicode does not create the images that the end users will see and use, as vendors take the technical code and render a particular aesthetic based on their platform, device, or operating standards and aesthetics (Unicode Consortium, 2018m).



Social uses of technical standards or the social production of technical standards?

Yochai Benkler notes, “Different technologies make different kinds of human action and interaction easier or harder to perform. All other things being equal, things that are easier to do are more likely to be done, and things that are harder to do are less likely to be done” [31]. Before emoji were standardized by Unicode, cell phones could display emoji-like characters through various keyboard extensions or applications, but without the guarantee that those with different cellular devices from yours would be able to see the image. With Unicode’s improvements to emoji standardization across devices and platforms emoji access also became incentivized. In a 2011 a New York Times article titled “Whimsical Texting Icons Get a Shot at Success” emoji are argued to be “on the verge of going mainstream in the United States, thanks in part to Apple’s latest update to its iPhone software” [32]. Apple’s 2011 iOS 5 update, which automatically installed an emoji keyboard, provided easy access to emoji for iPhone users, removing the two-step process of selecting and downloading an emoji-specific application to use. Wortham’s article makes a direct link to the technical standardization of emoji as a potential factor in Apple’s decision to include the emoji keyboard in iOS 5: “Apple declined to comment on its decision to add emoji, but it was most likely driven by a global standardization of the format last year that was meant to ensure that a picture of a cute cat will still look like a cute cat on a different phone in a different country” [33]. Android followed suit later in 2013, when it released the KitKat operating system which had a built in emoji keyboard (Bonnington, 2013).

The history of emoji is one where particular institutional choices, namely those of the Unicode Consortium and the companies, governments, and various institutions that make up its membership, produced particular consequences. The full members of the Consortium represent many of the key players in mobile technology, desktop computing, and software development: Apple, Google, Microsoft, IBM, Adobe, to name a few. It is reasonable to assume these companies would be invested in the kinds of technology that gain public traction and are used widely, and while this does not mean they are only invested in Unicode to develop standards that work with their products, what these companies gain through their involvement with Unicode is perhaps peripheral to the larger economic gains produced by global technical standards. For these companies, significant economic gain lies in developing a unified character standard, as a unified standard makes it easier for the products from these companies (be it hardware and software) to be sold to a global market. Programmer Steven Searle argues “Unicode did not become the dominant standard on account of its technological superiority alone (indeed, that in itself is questioned), but rather because of the alliance of U.S. firms supporting it” [34]. The popularity of emoji, and their compatibility across the various devices, platforms, and applications further emphasizes the usefulness of the technical standardization of these characters, for without a unified standard, emoji would not exist as they do today. As Janet Abbate notes “Standardization had obvious benefits, but the choice of any particular protocol as an international standard would also create winners and losers among the creators and users of network technology” [35]. Though none of these companies necessarily have direct monetary profit from the creation or application of emoji, there is a strong argument that devices, platforms, and applications that do not support emoji could be less attractive to the end user and thus it is in the corporate interest to ensure product compatibility. The technological standardization of emoji, while central to multi-device and platform proliferation, does not guarantee their use. However, emoji standardization was part of what made it possible for various social groups who were dissatisfied with the offerings to begin public conversations around desired changes to existing emoji designs, as well as the creation of entirely new emoji characters.

In early 2014, the lack of racial diversity in the canonized emoji set prompted online campaigns and vocal public dissatisfaction. A petition to diversify emoji was created on, which prompted a blogger from television network MTV’s ACT initiative to e-mail Apple executive Tim Cook to question the lack of diversity in emoji. In response Apple announced that it would work alongside the Consortium on a “technical solution” as they agreed that “there needs to be more diversity in the emoji character set” [36]. Subsequently, Unicode Standard 8, released in 2015, included a skin tone modifier which allowed users to choose a skin tone for any of emoji people, as well as the hand symbols emoji subset. The official proposal for emoji diversity, stated that though “emoji characters for people and body parts are meant to be generic” the precedent for emoji comes from Japan where the characters “are often shown with a light skin tone instead of a more generic (nonhuman) appearance, such as a yellow/orange color or a silhouette” [37]. This is one example where social dissatisfaction with emoji choices led to a technical change, which is increasingly how significant change to emoji have progressed, as demonstrated by the increase of professional female emoji, as well as the inclusion of more diverse types of food objects, outlined below.

In 2015, Always, a feminine hygiene brand, started an ad campaign titled “Like a Girl.” In March 2016 Always released a video advertisement titled “#LikeAGirl — Girl Emoji”. The premise of the ad was that “72 [percent] of girls feel that society limits them ... and sometimes these limiting messages can be found in unexpected subtle places like your phone” [38]. The ad argued emoji are one way girls express themselves in texts and online, but questioned whether emoji truly represented girls, asking young women what kind of emoji they would like to see added to better represent them. The ad was uploaded to YouTube on 2 March 2016 and went viral, racking up over 18,268,000 views by mid-April 2016. On 11 March 2016 Amy Butcher published an opinion piece in the New York Times titled “Emoji feminism” in which she noted that the majority of “professional” emoji figures were men. Butcher asks: “Where I wanted to know, was the fierce professor working her way to tenure? Where was the lawyer? The accountant? The surgeon? How was there space for both a bento box and single fried coconut shrimp, and yet women were restricted to a smattering of tired, beauty-centric roles?” [39] Unicode did not ignore the mounting frustration over the gendered nature of emoji content. Responding to Butcher’s op-ed piece, Mark Davis, Unicode co-founder and president (who also oversees the Emoji Subcommittee) replied to Butcher in kind, writing a follow up op-ed in the New York Times: “The non-profit Unicode Consortium ... has been working for nearly a year on making more emoji gender choices available, as Ms. Butcher suggests. The consortium posted a public call for feedback on the resulting proposal on [February] 29. This proposal would provide for male and female counterparts of the existing emoji, and is similar to the way skin tones for emoji are handled” [40]. This “call for feedback” is one Davis himself answered with a team of engineers at Google, proposing the “working women” emoji set. As these examples illustrate, though there is an established technical standard for Unicode characters, social groups and the broader public reacting to prior technical decisions can shift the direction of future technical code.

Another example of the power of social dissatisfaction is the dumpling emoji. Disappointed by the lack of a dumpling emoji designer Yiying Lu and journalist Jennifer 8. Lee set about to make one. While their proposal was ultimately successful and implemented into Unicode 10 in 2017, Lee’s experience with the rigours process led her to note that given the prevalence of dumplings in global cuisine from Japanese gyoza to Polish pierogi, “the fact there was no dumpling emoji told me whatever system was in place had failed” [41].

In the process of petitioning for the dumpling, Lu, Lee, and Jeanne Brooks, an ecosystem architect, founded Emojination, with the explicit goal of “[making] emoji approval an inclusive, representative process” due to the fact that “decision makers [of emoji] along the way are generally male, white, and engineers. They specialize in encoding. Such a review process certainly is less than ideal for promoting a vibrant visual language used throughout the world” [42]. Emojination has created successful emoji petitions for at least six emoji as of 2018 (see Figure 4) with an active public list of emoji ideas on their Web site that they encourage users to collaborate on.


Successful Emojination emoji proposals
Figure 4: Successful Emojination emoji proposals (


While the social dissatisfaction with emoji has provided an impetus for Unicode to consider diversifying the visual content of emoji, the influence that comes with full-membership in Unicode cannot be ignored. In 2016, the Unicode 9 update was slated to include a rifle emoji as part of a set of winter sport emoji set. Charlie Warzel, reporting for BuzzFeed News, wrote that “According to sources in the room, Apple started the discussion to remove the rifle emoji which had already passed into the encoding process for the Unicode 9.0 release this June [2016]” [43]. This was a somewhat significant moment, Warzel notes, because the vast majority of emoji proposals that pass to the point of being an “accepted candidate” are approved. While the discussion was not cited as contentious, subsequent headlines like the Guardian’s “Rifle emoji blocked from phones ‘after pressure from Apple’” (Hern, 2016) or the Canadian Broadcasting Corporation’s “Apple stops Unicode from releasing a rifle emoji” (O’Neil, 2016) framed the issue as one where Apple had the power, influence, and means to block a specific emoji from inclusion that had already been publicly circulated as an approved candidate.

The opposite is also observed, when companies who are members of the Unicode Consortium publicly endorse or propose the inclusion of a particular emoji or emoji set. In 2016 Google began a public campaign to include more professional women emoji. At the time, there had been growing public sentiment that the emoji characters of women were inadequate (as described earlier). While any individual, group, or corporation may propose emoji, the emoji set which showed working women in a variety of jobs (see Figure 5), was publicly branded as “Google’s” as the proposal of the emoji set was widely publicized (Bruner, 2016; Byford, 2016; Workman, 2016) and were even nominated for Design of the Year in 2017 by the Design Museum in London in 2017 (Knapton, 2017).


Google's proposed working women emoji
Figure 5: Google’s proposed working women emoji (in Knapton, 2017).


Proposed by a team of four Google employees, Sam Byford noted that “The team says it would like to get the new emoji by the end of 2016, and it probably has a good shot of achieving that goal — one member, Mark Davis, is co-founder and president of the Unicode Consortium” [44]. While stronger representation of any underrepresented group should be supported and encouraged, this example shows how companies that are full voting members of Unicode, like Apple, Google, Microsoft and others, will not hesitate to openly influence the direction of emoji development, but are also the ones who process their own, and other, proposals for new emoji. As this examination of emoji demonstrates, technical standardization increases the possibility of use, but social uses arguably drive the continued production of these technical standards, as increased and frequent use requires that users have the emoji they want to use included in the Standard. However, while social critique of the established “canon” of emoji has also driven modification, as both racial diversification and gender inclusive professional emoji signal, but the final decisions are still made by those that pay for the ability to do so.



Emoji: Making standards visible with a 😄

As noted above, Unicode co-founder and president Mark Davis states that emoji draw attention to an organization that has mostly been invisible. The work Unicode does, however, has made the Internet, and much of digital communication, visible. As the dominant standard for much character display, perhaps Unicode, its members, and its structure should not remain in the background any longer. Why are these companies, organizations, and institutions that pay for full membership investing in standards? Why should they be the ones to make these decisions? Nickerson and zur Muehlen argue that Internet standards, while enabling interaction, are not coercive. That is to say, that the incentive to adopt standards “comes from positive network effects and economies of scale” [45]. This is true of Unicode Standard, as it increasingly shapes communication in the digital world, as it is the gatekeeper to character availability for the majority of contemporary software and digital platforms. While there have been studies on the standardization of Internet protocol and user interface (Abbate, 1999; Hovav, et al., 2004; O’Connell, 2013; Pangalos, 1992), studying the standards that make individual characters possible has not been sufficiently explored. As the content of emoji becomes more visible, publicly contested, and a basis for various social causes, they foster a discussion of who decides what emoji are made, who is making decisions about character standards, and who decides what kinds of symbols and what languages make up the digital cannon. Should a membership fee be the only criteria for those who ultimately make these decisions? In many ways, English speakers take digital characters for granted as the Latin-based script that most English languages use is what the Internet has primarily used in its development [46]. The organizations that continue to maintain and develop standards are made up of predominantly North American technology companies that have a great deal to gain through maintaining standards that benefit their bottom line, and make a global market for their products possible.

In Inventing the Internet Abbate observes: “Tracing the history of the standards debate highlights the roles of the various interest groups that were involved in data communications during the formative years of the Internet. The outcome of this standards debate would shape the world of international networking in the 1980s and help set the stage for the Internet’s worldwide expansion in the 1990s” [47]. Emoji are an example of how standards are still an important component worth considering in contemporary critical Internet studies, because technical standards make certain languages and visual content visible, and perhaps occlude others, intentionally or not, from view. As the building blocks for digital communication character standards are fundamental, they do not just appear, and they were not always just there. Unicode’s codespace has 1,114,112 code points. While Unicode Standard 11 contains just over 137,300 characters, there are a finite number of code points, and as is Unicode policy, “once a character is encoded, it will not be moved or removed” (Unicode Consortium, 2018b). This means that those who make the decisions about what characters are coded into Unicode Standard are making choices that are permanent, and part of a finite number of possible characters. Unicode Standard is not the only way to display characters on digital devices, but its increasing proliferation and wide-spread adoption is significant, as the choices about what languages or visual material is included or excluded affect who gets to speak, and how. In the current Unicode model, those who have the money to pay for membership get to make these decisions, but in this type of model, who is left out?

What if the display of digital characters was conceptualized through Lawrence Lessig’s notion of the commons as “a resource to which anyone within the relevant community has a right to without obtaining the permission of anyone else” [48]? Then the question becomes not if minority languages or culturally specific emoji are coded into Unicode, but when. Considering the ability to speak, in either textual-linguistic or visual characters as a right, positions the ability to use digital communication as a public good, and not around concerns of the size of the population who might use specific character sets, or the assumed frequency of use. With respect to emoji specifically, the Consortium has successfully incorporated public frustration and feedback to create a more diverse set of visual characters, but emoji is only one small part of their mandate. As the popularity and publicity of emoji brings Unicode and its decision making practices into the public spotlight, the larger issue of representation and access at one of the most micro-digital levels becomes visible, and with this visibility, providing an opportunity to reconceptualize how to think about digital character standards. End of article


About the author

Bethany Berard is a Ph.D. candidate in communication at the School of Journalism and Communication at Carleton University in Ottawa, Canada.
E-mail: bethany [dot] berard [at] carleton [dot] ca



The author acknowledges the Social Science and Humanities Research Council of Canada for its financial support of her research, sincerely thanks Dwayne Winseck for comments on the first draft of this project, and thanks the generous and thoughtful peer reviewers whose comments made this paper stronger.



1. Pinch and Bijker, 1987, p. 30.

2. The original, or first emoji were produced for Japanese mobile carriers and designed by Shigetaka Kurita. The original 176 emoji were coded into Unicode 6, but since that large batch-import of emoji all proposals for new emoji characters have been adjudicated by a technical subcommittee of Unicode.

3. Winseck, 2016, p. 1,502. See also Mosco, 2009; Wasko, 2018.

4. Nickerson and zur Muehlen, 2006, p. 467.

5. Davis and Edberg, 2015, n. pag.

6. This is not a problem specific to computers, as the invention of the telephone saw a similar transition from phones that were network specific which proved problematic, thus necessitating a standardized protocol across the devices so individuals could call one another regardless of network (see Milton Mueller, Universal service: Competition, interconnection, and monopoly in the making of the American telephone system. Cambridge, Mass. : MIT Press, 1997).

7. Wu, 2000, p. 766. See also Blažic, et al., 1997.

8. John, 2013, p. 327.

9. Membership is regularly updated and can be viewed at

10. Unicode Consortium, 2018l, n. pag. Membership history can be viewed at

11. Unicode Consortium, 2012, p. 1.

12. EmojiOne’s mission statement is “to drive new emoji development and innovation forward.” A for profit company (though they have yet to turn a profit) that follows the Unicode Standard but has created an independent, open-sourced emoji set that is intentionally independent from any specific device or company, and is available for companies or individuals to license.

13. EmojiXPress is a keyboard application that allows users to send emoji and stickers, and is currently only available for iOS operating systems.

14. Luckerson, 2016a, n. pag.

15. Unicode Consortium, 2018b, n. pag.

16. Galloway, 2016, n. pag. See also Danesi, 2016, Negishi, 2014.

17. Davis and Edberg, 2015, n. pag. See also Danesi, 2017, p. 2.

18. Suignard, 2007, n, pag.

19. Davis and Edberg, 2015, n. pag.

20. Unicode Consortium, 2018d, n. pag. This number is debatable as Unicode states that some characters that render as symbols fit under the technical definition of emoji, but are not of the same cartoon aesthetic, and thus the average user would not identify these symbols as “emoji” proper. See also Unicode Consortium (2018a).

21. Unicode Consortium (2018g). See for the comprehensive list and (Unicode Consortium 2018d) for a charted breakdown of emoji in Unicode 11.

22. CLDR stands for Unicode Common Locale Data Repository, which “provides short descriptive names for characters across languages” (see for further information about CLDR short names). Unicode’s Common Locale Data Repository is a data repository that supplies the “building blocks” for software to support Unicode’s code (Unicode Common Locale Data Repository, 2018).

23. The procedure for submitting a new character outlined on Unicode’s Web site and can be referenced at, with specific guidelines for proposal of characters that are emoji, which can be found at

24. Emoji characters are grouped into eight broad categories (each with multiple subcategories), 1) Smileys and People, 2) Animals and Nature, 3) Food and Drink, 4) Travel and Places, 5) Activities, 6) Objects, 7) Symbols, and 8) Flags. Each category has similar emoji grouped together to organize emoji in such a way that users can easily find specific emoji. Unicode Consortium, 2018e, n. pag. See

25. Luckerson, 2016b, n. pag.

26. Interestingly, in 2016 the third and fourth criteria inclusion criteria for the expected usage level were emotional content and persistence of usage in the future respectively. The move away from emotional content perhaps indicates a shift away from viewing emoji as primarily emotive in their communicative potential. Additionally that persistence of future use is not a criteria for inclusion indicates the potential popularity of emoji is no longer of primary concern.

27. To date ASLized sells the Signily keyboard for US$0.99 to fund ’the emoji project’ and raise the funds to becomes an associate member of the Unicode Consortium (see

28. For the full story from Taco Bell’s perspective see


30. Pinch and Bijker, 1987, p. 40.

31. Benkler, 2006, p. 17.

32. Wortham, 2011, n. pag.

33. Wortham, 2011, n. pag.

34. Searle quoted in John, 2013, p. 329.

35. Abbate, 1999, p. 148.

36. Stampler, 2014, n. pag. See also Kelion, 2014.

37. Quoted in Stark and Crawford, 2015, p. 7.

38. “Always Like A Girl” advertisement, 2016, n. pag.

39. Butcher, 2016, n. pag.

40. Davis, 2016, n. pag.

41. McCracken, 2017, n. pag.


43. Warzel, 2016, n. pag.

44. Byford, 2016, n. pag.

45. Nickerson and zur Muehlen, 2006, p. 468. See also Schoechle, 2009; Weiser, 2001.

46. This has been referred to as “computer-mediated-colonization” by Charles Ess (quoted in John, 2013, p. 322). Brenda Danet and Susan C. Herring (2006) also raise the question “typographic imperialism” in the English-based ASCII Internet transmission protocols.

47. Abbate, 1999, p. 148.

48. Lessig, 2001, p. 20.



Janet Abbate, 1999. “The Internet in the international standards arena,” In: Janet Abbate. Inventing the Internet. Cambridge, Mass.: MIT Press, pp. 147–180.

Always, 2016. “Always #LikeAGirl — Girl emoji” (2 March), at, accessed 15 April 2016.

Naomi S. Baron and Rich Ling, 2011. “Necessary smileys & useless periods: Redefining punctuation in electronically-mediated communication,” Visible Language, volume 45, numbers 1-–, pp. 45–67, and at, accessed 10 August 2016.

Yochai Benkler, 2006. The wealth of networks: How social production transforms markets and freedom. New Haven, Conn.: Yale University Press.

Borka Jerman-Blažic, Konstantin Chuguev, and Andrj Gogala, 1997. “Standard specification extensions for provision of language and character enabled server,” Computer Communications, volume 20, number 11, pp. 927–936.
doi:, accessed 20 April 2018.

Christina Bonnington, 2013. “How to get the emoji keyboard on your iOS or Android device,” Wired (13 November), at, accessed 2 July, 2018.

Jonah Bromwich, 2015. “How emoji find their way to phones,” New York Times (20 October), at, accessed 8 April 2018.

Raisa Bruner, 2016. “Emoji will have exciting new roles for women,” Time (15 July), at, accessed 8 April 2018.

Amy Butcher, 2016. “Emoji feminism,” New York Times (11 March), at, accessed 8 April 2018.

Sam Byford, 2016. “Google proposes new set of emoji to better represent professional women,” The Verge (10 May), at, accessed 8 April 2018.

David Crystal, 2006. “The language of the Web,” In: David Crystal. Language and the Internet. Second edition. New York: Cambridge University Press, pp. 203–237.

Marcel Danesi, 2016. The semiotics of emoji: The rise of visual language in the age of the Internet. London: Bloomsbury.

Brenda Danet and Susan C. Herring, 2006. “Introduction: The multilingual Internet,” Journal of Computer-Mediated Communication, volume 9, number 1.
doi:, accessed 2 July 2018.

Damon Darlin, 2015. “America needs its own emojis,” New York Times (7 March), at, accessed 8 April 2018.

Mark Davis, 2016. “Emoji gender choices: Letter to the editor,” New York Times (23 March), at, accessed 8 April 2018.

Mark Davis and Peter Edberg, 2015. “Unicode emoji,” Unicode Technical Report, number 51, at, accessed 20 April 2018.

Daantje Derks, Arjan E. R. Bos, and Jasper von Grumnkow, 2008. “Emoticons and online message interpretation,” Social Science Computer Review, volume 26, number 3, pp. 379–388.
doi:, accessed 20 April 2018.

Daantje Derks, Arjan E. R. Bos, and Jasper von Grumnkow, 2007. “Emoticons and social interaction on the Internet: The importance of social context,” Computers in Human Behavior, volume 23, number 1, pp. 842–849.
doi:, accessed 20 April 2018.

Durex Canada, 2015. “Petition for #CondomEmoji ad,” retrieved from author’s Facebook newsfeed, accessed 22 November 2015, and at, accessed 10 August 2018.

Sydney Ember, 2015. “Brands woo millennials with a wink, an emoji or whatever it takes,” New York Times (27 September), at, accessed 8 April 2018.

Emojination, at, accessed 2 July 2018.

Vyvyan Evans, 2015. “Signs of our times: Why emoji can be even more powerful than words,” The Conversation (6 March), at, accessed 20 April 2018.

Paul Galloway, 2016. “The original emoji set has been added to the Museum of Modern Art’s collection,” Museum of Modern Art (26 October), at, accessed 20 April 2018.

Anthony Garrison, Dirk Remley, Patrick Thomas, and Emily Wierszewiski, 2011. “Conventional faces: Emoticons in instant messaging discourse,” Computers and Composition, volume 28, number 2, pp. 112–125.
doi:, accessed 20 April 2018.

Vindu Goel, 2015. “Facebook to test emoji as reaction icons,” New York Times (8 October), at, accessed 8 April 2018.

Christina Haas, Pamela Takayoshi, Brandon Carr, Kimberley Hudson, and Ross Pollock, 2011. “Young people’s everyday literacies: The language features of instant messaging,” Research in the Teaching of English, volume 45, number 4, pp. 378–404.

Alex Hern, 2016. “Rifle emoji blocked from phones ‘after pressure from Apple’,” Guardian (20 June), at, accessed 8 April 2018.

Robert D. Hof, 2016. “Picture this: Marketers let emoji do the talking,” New York Times (6 March), at, accessed 8 April 2018.

Anat Hovav, Ravi Patnayakuni, and David Schuff, 2004. “A model of Internet standards adoption: The case of IPv6,” Information Systems, volume 14, number 3, pp. 265–294.
doi:, accessed 20 April 2018.

Nicholas A. John, 2013. “The construction of the multilingual Internet: Unicode, Hebrew, and globalization,” Journal of Computer-Mediated Communication, volume 18, number 3, pp. 321–338.
doi:, accessed 20 April 2018.

Leo Kelion, 2014. “Apple seeks greater emoji racial diversity,” BBC News (26 March), at, accessed 8 April 2018.

Kyongsok Kim, 1992. “A future direction in standardizing international character codes — with a special reference to ISO/IEC 10646 and Unicode,” Computer Standards & Interfaces, volume 12, number 3, pp. 209–221.

Elizabeth Kirley and Marilyn McMahon, 2017. “The emoji factor: Humanizing the emerging law of digital speech,” at, accessed 20 April 2018.

Sarah Knapton, 2017. “Google ‘professional women’ emoji nominated for design of the year,” Telegraph (16 August), at, accessed 8 April 2018.

Matthew Knott, 2015. “Emoji diplomacy? DFAT asked meaning behind Julie Bishop’s use of a red-faced emoji to describe Vladimir Putin,” Sydney Morning Herald (22 October), at, accessed 8 April 2018.

Lawrence Lessig, 2001. The future of ideas: The fate of the commons in a connected world. New York: Random House.

Raymond Liu and John Lions, 1998. “Distributed multilingual applications of the OSI architecture,” Computer Standards & Interfaces, volume 19, number 1, pp.9–29.
doi:, accessed 20 April 2018.

Victor Luckerson, 2016a. “Meet the 63-year-old in charge of approving new emoji,” Time (2 March), at, accessed 8 April 2018.

Victor Luckerson, 2016b. “The inside story of why the world is being blessed with a ‘Colbert emoji’,” Time (25 March), at, accessed 8 April 2018.

Harry McCracken, 2017. “How the dumpling democratized emoji,” Fast Company (10 August), at, accessed 2 July 2018.

Kazuko Miyake, 2007. “How young Japanese express their emotions visually in mobile phone messages: A sociolinguistic analysis,” Japanese Studies, volume 27, number 1, pp. 53–72.
doi:, accessed 20 April 2018.

Vincent Mosco, 2009. The political economy of communication. Second edition. London: Sage.

Milton Mueller, 1997. Universal service: Competition, interconnection, and monopoly in the making of the American telephone system. Cambridge, Mass. : MIT Press.

Mark Needleman, 2000. “The Unicode standard,” Serials Review, volume 26, number 2, pp. 51–54.
doi:, accessed 20 April 2018.

Mayumi Negishi, 2014. “Meet Shigetaka Kurita, the father of emoji,” Wall Street Journal (26 March), at, accessed 8 April 2018.

Jeffrey Nickerson and Michael zur Muehlen, 2006. “The ecology of standards processes: Insights from Internet standard making,” MIS Quarterly, volume 30, pp. 467–488.
doi:, accessed 10 August 2018.

Oxford Dictionaries, 2015. “Oxford Dictionaries word of the year 2015 is ...” (16 November), at, accessed 8 April 2018.

John O’Connell, 2013. “An IT perspective on standards, service architectures and platforms,” In: Emmanuel Bertin, Noel Crespi, and Thomas Magedanz (editors). Evolution of telecommunication services. Lecture Notes in Computer Science, volume 7768. Berlin: Springer-Verlag, pp. 118–137.
doi:, accessed 10 August 2018.

Lauren O’Neil, 2016. “Apple stops Unicode from releasing a rifle emoji, gun advocates get mad,” Canadian Broadcasting Corporation (CBC) News (22 June), at, accessed 8 April 2018.

George J. Pangalos, 1992. “Standardization of the user interface,” Computer Standards & Interfaces, volume 14, number 3, pp. 223–229.
doi:, accessed 20 April 2018.

Trevor Pinch and Wiebe Bijker, 1987. “The social construction of facts and artifacts: Or how the sociology of science and the sociology of technology might benefit each other,” In: Wiebe E. Bijker, Thomas P. Hughes, and Trevor J. Pinch (editors). The social construction of technological systems: New directions in the sociology and history of technology. Cambridge, Mass.: MIT Press, pp. 17–50.

Timothy Schoechle, 2009. Standardization and digital enclosure: The privatization of standards, knowledge, and policy in the age of global information technology. Hershey, Pa.: Information Science Reference.

Signily, “Signily — ASL keyboard app,” at, accessed 8 April 2018.

Karianne Skovholt, Anette Grønning, and Anne Kankaanranta, 2014. “The communicative functions of emoticons in workplace e-mails: :-),” Journal of Computer-Mediated Communication, volume 19, number 4, pp. 780–797.
doi:, accessed 20 April 2018.

Laura Stampler, 2014. “Apple is finally working on racially diverse emoji that aren’t complete stereotypes,” Time (27 March), at, accessed 8 April 2018.

Luke Stark, and Kate Crawford, 2015. “The conservatism of emoji: Work, affect, and communication,” Social Media + Society.
doi:, accessed 20 April 2018.

Michel Suignard, 2007. “Japanese TV symbols: Input to ISO/IEC 10646:2003,” Unicode (18 September), at, accessed 2 July 2018.

Taco Bell, 2015. “Taco emoji: We did it,” Taco Bell Stories, at, accessed 8 April 2018.

Alina Tugend, 2015. “The Ad Council adapts to stay relevant in an age of social action,” New York Times (22 November), at, accessed 8 April 2018.

Unicode Common Locale Data Repository, 2018. “Characters names and keywords (emoji),” at, accessed 2 July 2018.

Unicode Consortium, 2018a. “Unicode 11.0.0” (5 June), at, accessed 2 July 2018.

Unicode Consortium, 2018b. “Unicode character encoding stability policies” (23 June), at, accessed 2 July 2018.

Unicode Consortium. 2018c. “Comparison of membership levels,” at, accessed 8 April 2018.

Unicode Consortium. 2018d. “Emoji counts, v11.0,” at, accessed 2 July 2018.

Unicode Consortium. 2018e. “Emoji ordering, v11,” at, accessed 8 April 2018.

Unicode Consortium. 2018f. “Examples of emoji rendering across various devices/applications/vendors,” at, accessed 8 April 2018.

Unicode Consortium. 2018g. “Full emoji list, v.11.0,” at, accessed 8 April 2018.

Unicode Consortium. 2018h. “History of Unicode release and publication dates,” at, accessed 2 July 2018.

Unicode Consortium. 2018i. “Submitting character proposals,” at, accessed 8 April 2018.

Unicode Consortium. 2018j. “Submitting emoji proposals,” at accessed 8 April 2018.

Unicode Consortium. 2018k. “The Unicode Consortium members,” at accessed 8 April 2018.

Unicode Consortium. 2018l. “Unicode Consortium membership history,” at, accessed 8 April 2018.

Unicode Consortium. 2018m. “UTC consideration,” at, accessed 8 April, 2018.

Unicode Consortium. 2016. “Submitting emoji character proposals,” at, accessed 15 April 2016.

Unicode Consortium, 2012, “Unicode, Inc. conflict of interest policy” (3 February), at, accessed 8 April 2018.

Unicode Consortium, 2009. “Approved minutes of the UTC 118 / L2 215 joint meeting” (12 May), at, accessed 2 July 2018.

Charlie Warzel, 2016. “Thanks to Apple’s influence, you’re not getting a rifle emoji,” Slashdot (17 June), at, accessed 8 April 2018.

Janet Wasko, 2018. “Studying political economies of communication in the twenty-first century,” Javnost — The Public, volume 25, numbers 1–2, pp. 233–239.
doi:, accessed 2 July 2018.

Benjamin Weiser, 2015. “At Silk Road trial, lawyers fight to include evidence they call vital: Emoji,” New York Times (28 January), at, accessed 28 January, 2015.

Philip J. Weiser, 2001. “Internet governance, standard setting, and self-regulation,” Northern Kentucky Law Review, volume 28, number 4, pp. 822–846, and at, accessed 2 July 2018.

Dwayne Winseck, 2016. “Political economy,” In:: Klaus Bruhn Jensen (editor-in-chief). International encyclopedia of communication theory and philosophy. Hoboken, N.J.: Wiley-Blackwell, pp. 1,500–1,515.
doi:, accessed 10 August 2018.

Karen Workman, 2016. “Emoji would show women doing more than painting their nails,” New York Times (12 May), at, accessed 8 April 2018.

Jenna Wortham, 2011. “Whimsical texting icons get a shot at success,” New York Times (6 December), at, accessed 8 April 2018.

Pei-Chi Wu, 2000. “Transition from national standards to Unicode: multilingual support in operating systems and programming languages,” Software: Practice and Experience, volume 30, number 7, pp. 765–774.
doi:<765::AID-SPE317>3.0.CO;2-N, accessed 20 April, 2018.

Katie Zavadski, 2015. “Brooklyn teen arrested for emoji-laden threats against NYPD,” New York Magazine (23 January), at, accessed 23 November 2015.

Appendix: Comparison of Unicode Consortium membership levels (Unicode, 2018c)


Unicode, 2018, Comparison of Unicode Membership Levels
See: Unicode, 2018c. “Comparison of Unicode membership levels,” at, accessed 8 April 2018..



Editorial history

Received 8 August 2018; accepted 9 August 2018.

Creative Commons License
This paper is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

I second that emoji: The standards, structures, and social production of emoji
by Bethany Berard.
First Monday, Volume 23, Number 9 - 3 September 2018