How social media supports hashtag activism through multivocality: A case study of #ILookLikeanEngineer
First Monday

How social media supports hashtag activism through multivocality: A case study of #ILookLikeanEngineer by Aqdas Malik, Aditya Johri, Rajat Handa, Habib Karbasian, and Hemant Purohit



Abstract
Although research on different hashtag activism campaigns abounds, no study has looked at how different affordances of social media support a single campaign. We use data from a hashtag activism campaign, #ILookLikeAnEngineer, launched to showcase diversity within engineering workforce, to examine how different elements of a campaign blend together. We specifically identify three distinct but interconnected ways in which social media supports activism: 1) modality — it allows users to participate through text, photos, and links; 2) messaging — it allows users to post and support multiple though related topics; and 3) actors — it provides a voice to different participants (individuals/organizations, men/women). Our analysis supports the idea that multivocality — the core idea that people leverage multiple ways of participating — is the key to campaign success. Our analysis of 19,492 original tweets and 89,650 retweets shows that multivocality allowed the campaign to receive support not just from individuals but from large corporations, media, and NGOs, who were able to share their perspective using their preferred modality giving rise to a new form of digital polyphonic narrative that supports their agenda.

Contents

Introduction
Research study
Findings and discussion
Conclusion

 


 

Introduction

The use of Twitter and other platforms for activism — often termed as “hashtag activism” — has become highly prevalent. There are a number of factors that allow these campaigns to proliferate — Arab Spring (Sjoberg and Whooley, 2015); Ferguson (Bonilla and Rosa, 2015; Cowart, et al., 2016); and, Occupy Wall Street (Conover, et al., 2013). In this paper we examine how different elements of a campaign — its messages, its modality, and its actors — converge to make it successful.

A core characteristic of social movements is that they bring together people and organizations around a central idea or goal providing a sense of collective identity (Polletta and Jasper, 2001). Whether it is large scale movements such as the feminist movement or smaller activism efforts, collective identity plays a critical role in coalescing participants (Taylor and Whittier, 1992). Although social movements are guided by a collective sense of identity (Flesher Fominaya, 2010; Polletta and Jasper, 2001; Taylor and Whittier, 1992), scholars have long argued that their success often depends on their ability to bring together a range of opinions and engage a diverse set of participants, thereby providing a voice to the marginalized (Benford and Snow, 2000; Shirazi, 2013). This ability of a movement to support multivocality — an inherent multiplicity of viewpoints and perspectives — provides a movement momentum and success (Bakhtin, 1981; Baptista, et al., 2017). In other words, participation in social movements is a lot more nuanced and diverse especially since any movement or activism campaign is a contested arena with often shifting meanings (Flesher Fominaya, 2010). These multiple voices enable organizing as they allow participants who have diverse opinions but related interests to identify with and work towards a common goal. Furthermore, such ambiguity is a resource when it comes to mobilizing people as people who might hold slightly diverse views stick together (Belova, et al., 2008).

The concept of multivocality has emerged from the theoretical ideas of Bakhtin whose work, especially The dialogic imagination (Bakhtin, 1981), advanced the idea of polyphony or “multi-voicedness”. The term polyphony is opposed to the term monologic and according to Bakhtin, the canonized genres like the epic, the tragedy, and the lyric are monologic as they try to establish a single style and a unified voice, which expressed a singular world-view. Bakhtin (1984) argued that in novels, particularly the works of Dostoevsky, different authorial points of view allow different ideologies to emerge thereby forcing the reader into a higher level of participation with the text. Furthermore, in a polyphonic novel is a variety of conflicting ideological positions are given a voice without being placed and judged by an authoritative authorial voice (Gardiner, 2003). The multivoiced nature of fiction allows different ideological perspectives to enter the novel giving rise to what Bakhtin’s termed as “dialogics” or the process by which meaning is evolved out of interactions among the author, the work, and the reader. These elements are in turn influenced by the context in which they are placed, i.e., by the social and political forces influencing them. Within the literature on organizations and organizing, Bakhtin’s ideas overall and that of polyphony or multivocality has found significant uptake (Belova, 2006; Belova, et al., 2008; Bouwen and Steyaert, 1999). Scholars have used these ideas both to analyze organizations as discursive spaces and also as a textual strategy in writing research narratives. The presence of multiple voices, especially if it is supported by listening from those with different perspectives, provides a natural context for organizing (Belova, 2006).

The advent of social media — where different elements of a narrative and multiple authors can be combined — provides a fertile ground to better understand how diverse messages and memberships converge in support of a movement. Although in of itself, social media is not a text similar to a novel, yet, activism campaigns on social media have some similarities with a text such as a novel in their overall structure. There are many voices present, there are different ideologies represented, and a user is similarly engaged with a campaign as a reader might be with a novel. Social media, inherently, empowers voices that are traditionally marginalized such as ethnic factions, religious groups, women, and disabled (Kim and Miranda, 2011; Moen and Smørdal, 2010; Proskurnia, et al., 2016). Social media also allows near synchronous participation through multiple content forms, such as text, audio, photo, and video (Batson, 1990; Cowart, et al., 2016; Malik, et al., 2016). The use of social media transcends geography and allows bundling with other social media channels (Bonilla and Rosa, 2015). Finally, it provides participants the ability to engage and express in diverse ways such as retweets, favorites, hashtags, replies, and mentions. These different elements have played a critical role in the success of many of campaigns including #OccupyWallStreet, #IdleNoMore, #BlackLivesMatter, and #Ferguson (Callison and Hermida, 2015; Conover, et al., 2013; Cowart, et al., 2016; Yang, 2016).

In this paper, we employ the lens of multivocality to better understand how these different elements converge within a single hashtag activism campaign. We examine the Twitter campaign #ILookLikeanEngineer (ILLAE) to explore how affordance for multivocality supports activism.

Drawing from the prior work (Bonilla and Rosa, 2015; Callison and Hermida, 2015; Himelboim and Han, 2014), we identify three primary mechanisms in which multivocality affordances can be contextualized to a Twitter-based activist campaign (as well as other social media platforms and campaigns). First, how campaigners and activists of the movement utilized different content modalities (e.g., text, photos, or videos) and which of those modes (or their combination) was most engaging. Second, by using these different modalities what kind of discussion topics surfaced during the campaign and how people reacted to them. Third, identification of how key participants lead the campaign through different forms of content modalities and messages. We address the following questions: 1) Which mode of content drives participation of various actors in the campaign; 2) What messages are shared and discussed during the campaign; and, 3) Who are the active and notable tweeters that trigger participation and sustain the campaign?

 

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Research study

The hashtag activism campaign #ILookLikeAnEngineer was the brainchild of a U.S. based software engineer Isis Wenger. The hashtag was born out of her frustration with how people reacted online to an off-line recruitment advertisement by her company OneLogin™ that featured her on billboards on public transport areas. On the Web, many users, mostly males, reacted to the billboard by saying that she cannot really be an engineer or that the company used a picture of a female engineer solely to attract male applicants. Isis wrote a blog post about her experience that went viral and called for supporters to coalesce around her efforts to broaden the depiction of what an engineer looks like, hence the hashtag #ILookLikeAnEngineer. #ILookLikeanEngineer campaign was later adopted by similar movements led by women in other professions such as: #ILookLikeaSurgeon, #IlookLikeaPathologist, and #ILookLikeaHistorian.

Data collection

The data was collected in two phases. In the first phase, we collected the dataset using Twitter streaming API based on three seed hashtags — #ILookLikeAnEngineer, #LookLikeAnEngineer, and #LookLikeEngineer — as we had found instances of all of them being used in conjunction. The time frame for the data ranged from 3 August 2015, the day the hashtag was first used, until 15 October 2015, which is about two months after the initial surge of the campaign. In the second phase, we recollected the tweets data from Twitter using Search API a year after the campaign started to have a reliable and streamlined retweets/favorites count. The final dataset consists of 19,492 original tweets and 89,650 retweets which were favorited 142,858 times at the time the tweets were recollected. The tweets metadata collected is composed of: tweet text, retweet count, favorite count, time of the tweet, user name, screen name, location, followers, following, likes, and number of statuses.

 

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Findings and discussion

Content modality

In order to access the content modality of the campaign the tweets were categorized into four groups: a) Text only tweets; b) Text with link tweets; c) Text with photo tweets; and, d) Text with link and photo tweets. Tweet distribution for each category is presented in Table 1. A detailed analysis of the categorization of content modality indicates that almost half of the original tweets contained text and links, followed by tweets that contain text and photos. In total around two-thirds of the original tweets fall in this category, indicating the importance of photos and links in addition to tweet text. Further examination of retweets and favorites showed that tweets containing a photo stand clearly apart from other modalities. Although only around 40 percent of the original tweets contain an image together with text, a link, or both, a majority of the most retweeted tweets (85 percent) contained a photo either as a combination with text, a link, or with both. A majority of retweets (56.3 percent) and favorites (66.5 percent) tweets contain a photo.

The main implication of this study from the content modality perspective is that users prefer to embed photos and links within tweets. In the context of this campaign, appending additional content not only enabled them to express and relate themselves (through photos) to the campaign, but they were also able to provide additional information (through URLs). Furthermore, the tweets embedded with a photo generated higher level of engagement as they were retweeted and favorited significantly more than other forms of content. Based on the findings from the content modality analysis, we believe that using photos in tweets can be more engaging in Twitter-based campaigns, similar to findings in Cowart, et al. (2016), Malik, et al. (2016), Milner (2013), and Rainie, et al. (2012).

 

Table 1: Tweets categorization according to content modality.
 TextText+LinkText+PhotoText+Link+PhotoDataset
Tweets2580
(13.24%)
9130
(46.84%)
5541
(28.43%)
2241
(11.50%)
19492
Retweets2994
(3.34% )
17114
(19.09%)
50447
(56.27%)
19095
(21.30%)
89650
Favorites6071
(4.25%)
17514
(12.26%)
94930
(66.45%)
24343
(17.04%)
142858

 

Campaign messaging

To understand campaign messaging we undertook the following analyses: We used Latent Dirichlet Allocation (LDA), an unsupervised machine learning technique, for identifying topics related to tweets (Blei, et al., 2003; Schaal, et al., 2012). As a preprocessing step, we removed parts of tweet that provided us no or less information about the context like determiner (the, a, an), hashtags, hyperlinks, and usernames. We then applied the LDA model iteratively with different number of topics to the entire dataset and identified the optimal number of topics based on maximum log-likelihood. Based on this process, the final output resulted in six topics that capture the conversations in the tweets (see Figure 1). Table 2 provides examples of each theme as summarized in following.

 

Extracted topics of the campaign through LDA
 
Figure 1: Extracted topics of the campaign through LDA.

 

 

Table 2: Identified themes for the campaign.
ThemeExample tweet
Event participationThe #ILookLikeAnEngineer Community Hosted One Of The Most Powerful, Inspiring Tech Events I’ve via @techcrunch
Challenging stereotypes in tech industry #ilooklikeanengineer wants to challenge your ideas about who can work in tech — The Washington Post
Ada Lovelace day celebrationsMonday night I DJ at @ThoughtWorks NY as we honor Ada Lovelace #ALD15 for her 200th birthday #ILookLikeAnEngineer
Diversity in tech workforce#ILookLikeAnEngineer Movement Sparks Outpouring of Solidarity for Tech’s Diversity
Campaign praise and promotionIt is great that #engineers, and especially women #engineers are getting some exposure through twitter #ILookLikeAnEngineer keep it going!
Campaign strategy#ILookLikeAnEngineer spreads from Twitter to billboards as #womenintech respond to ad critics. #tech #girlswhocode

 

1. Event call and participation

The campaign was supported by a live event that was hosted on 13 August to raise funds for at least one massive #ILookLikeAnEngineer billboard to be erected in San Francisco. People were inspired by the event to tweet that featured the campaign initiator among other known speakers.

2. Challenging stereotypes in the tech industry

In addition to portraying diversity amonst engineers, the tweets also focused on motivating people to challenge stereotypes — a kind of call to action — that went beyond just highlighting contributions by women, illustrating diversity and encouraging concrete change.

3. Ada Lovelace Day celebrations

A number of tweets related to the Ada Lovelace Day celebration, held annually to recognize her contributions to programming and computers. During the campaign the event took on an additional meaning, as it marked her two-hundredth birthday (Lovelace was born on 10 December 1815).

4. Diversity in tech workforce

The campaign message moved from just being about women in engineering to overall diversity within the engineering workforce. Participants started expressing multiple ways marking diversity, such as their achievements that include not just being an engineer or knowing how to code but also their hobbies, interests, and families (e.g., “Love the UNITY and DIVERSITY of my team as we strive to bring ideas into reality #ILookLikeAnEngineer #MaternityHIT”).

5. Campaign praise and promotion

The campaign also received a strong support from a number of entities who appreciated the basic notions of the campaign. Participants praised the Twitter based campaign as they were able to hear opinions and thoughts of others facing similar challenges.

6. Campaign strategy

In the initial phases the campaign organizers and other users discussed the campaign and its strategy (e.g., “Let’s post a photo”). This was followed by discussion of other ideas that could generate responses, such as posting a large billboard in Silicon Valley.

Overall, from a standpoint of campaign messaging, we were able to identify a number of different yet converging conversational themes that reinforced the overall aims of the campaign. Through tweets, users from different backgrounds shared their personal stories and information on the contributions of women engineers to the society, and as a result supported the campaign.

Diversity of actors

Network analysis

To understand the role of different users within the community we carried out network analysis, using Gephi (Bastian, et al., 2009). In our network a node represented a user and an edge represented an interaction between two users. Given two user nodes A and B, a directional edge was created from A to B if ‘A retweeted or mentioned or replied to B’ and the edge weight was assigned by the weighted sum of frequency of the specific interaction (retweeting another user’s post, or mention of another user in a post, or reply to another user’s post). To identify active users we used degree centrality and of the top 25 users identified within the network, nine or 36 percent were large organizations, seven or 28 percent were individuals, and six or 24 percent were media outlets. The hashtag originator Isis Wenger ranked at the top of the list and campaign manager Michelle Glauser also made it to the list. Organizations making the list included Tesla, Intel, Ford, Caterpillar, and Microsoft. In the media category, besides mainstream media companies such as BBC, New York Times, and Fortune, there were a number of technology news and non-traditional media outlets such as Tech Crunch, Blavity, and Buzzfeed. Two NGOs ended up in the dominant list of 25 influencers (SWEtalk — Society of Women Engineers, and WomenWhoCode); both focus on supporting women engineers. A majority of the users were verified users (76 percent). The high number of verified users signifies the influence of these users in promoting the movement.

Actively retweeted users

Although organizations constituted a large portion of the prominent users’ list based on network influence, their impact in other indices of network popularity was limited. Only one organization was present in the list of top 20 retweets, indicating a lack of influence on other users, in spite a high number of followers for organizations. Tweets by individuals were highly popular and were retweeted extensively; individuals constitute 60 percent of the 20 most retweets count. Some of these individuals are well known, such as astronaut Scott Kelly, software engineer Tracy Chou, and campaign founder Isis Wenger; many individuals were not (e.g., Marcos Caceres and Jolene Hayes). This indicates the importance of involvement from individuals in campaign promotion and diffusion. Furthermore, 25 percent of the most retweeted tweets originated from media outlets (e.g., Tech Crunch, Buzzfeed) indicating that their participation is also necessary to diffuse content to niche communities of practice. With respect to users of retweets, a slight majority of the entities were verified (55 percent). In general, non-verified users had fewer followers limiting the reach of their tweets.

Actively favorited users

Similarly, among retweets, the favorite counts projected a comparable picture. Individuals dominated this category too, as out of the 20 most favorited tweets, 60 percent of them were tweeted by individuals. Organizations, media, NGO/communities, and universities held the remaining. Similarly, tweets of verified and non-verified were favorited almost equally. Finally, all of the tweets in the most favorited list contained a photo, which was quite similar to the findings in the case of most retweeted tweets. Visual content in tweets held a highly significant value and made tweets more appealing. In the context of this campaign, an overwhelming majority of photos were of women engineers working or engaged in routine daily activities, such as spending time with their families (Figure 2).

 

Collage of images in tweets
 
Figure 2: Collage of images in tweets.

 

These pictures are closer to reality and many can relate to them at some level. Some of these pictures also portray the contributions of women engineers to the workforce. Overall our findings from the most favorited and retweeted tweets were in agreement that, for the online discourse related to this campaign, individuals (ordinary citizens and to some extent notable personalities) predominated over other entities, such as organizations and media. The majority of media and organizational accounts were verified, indicating that non-individual entities participating in this movement were popular and reputable entities that helped the campaign to grow and deliver its basic message.

Finally, participation and active involvement in conversations were not only initiated by female engineers, but by a number of other entities (large multinationals, media outlets, males, African-Americans, and Hispanic women). These efforts stimulated momentum to the campaign. In sum, various affordances of multivocality provided by Twitter led the campaign initiators to successfully propagate their message of diversity in engineering.

 

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Conclusion

In this study, we analyzed participation during a hashtag activism campaign, #ILookLikeanEngineer, to identify how the affordances of social media supported the campaign. We found that campaigners and activists used different modes to express themselves as well as engage other users towards the campaign through text, photos, and external links to other sources of information. Images gained the highest engagement of all modes. Second, to voice their support and opinions, Twitter also facilitated the campaign initiator and participants to share a wide range of ideas and messages. Users were engaged in a diverse range of viewpoints, ranging from challenging stereotypes in the tech industry to appreciating the overall aims of the campaign and campaign initiators. Finally, these modalities and messages were initiated and responded by a diverse range of participants, supporting different and diverse voices. Overall, through our analysis we found strong support for the idea that social media allows multivocality, leading to a successful campaign. End of article

 

About the authors

Aqdas Malikis a postdoctoral research fellow in the Department of Information Sciences and Technology at George Mason University.
E-mail: malik [dot] aqdas [at] gmail [dot] com

Aditya Johri is an associate professor in the Department of Information Sciences and Technology at George Mason University
E-mail: johri [at] gmu [dot] edu

Rajat Handa is a research fellow in the Department of Information Sciences and Technology at George Mason University .
E-mail: rhanda [at] gmu [dot] edu

Habib Karbasian is a Ph.D. student in the Department of Information Sciences and Technology at George Mason University.
E-mail: hkarbasi [at] gmu [dot] edu

Hemant Purohit is an assistant professor in the Department of Information Sciences and Technology at George Mason University.
E-mail: hpurohit [at] gmu [dot] edu

 

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Editorial history

Received 22 May 2018; accepted 20 October 2018.


Creative Commons License
“How social media supports hashtag activism through multivocality: A case study of #ILookLikeanEngineer” by Aqdas Malik, Aditya Johri, Rajat Handa, Habib Karbasian, and Hemant Purohit is licensed under a Creative Commons Attribution 4.0 International License.

How social media supports hashtag activism through multivocality: A case study of #ILookLikeanEngineer
by Aqdas Malik, Aditya Johri, Rajat Handa, Habib Karbasian, and Hemant Purohit.
First Monday, Volume 23, Number 11 - 5 November 2018
https://firstmonday.org/ojs/index.php/fm/article/view/9181/7608
doi: http://dx.doi.org/10.5210/fm.v23i11.9181





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