Digital platforms such as Twitter enable people to interact with and influence one another, producing emergent phenomena. This study addresses the Twitter followership phenomenon. Focus groups and qualitative analyses were employed to generate insights into the Twitter followership phenomenon. Likely the first study in this domain, this research is the basis for future followership research on digital platforms and indicates the need for continued attention to this domain.Contents
Introduction
Literature review
Methodology
Results
Discussion
Limitations and implications
Conclusion
Digital platforms have contributed to the transformation of the nature of individuals and, by extension, society (Attai, et al., 2016; Garcia, et al., 2017; Murthy, 2018; Weller, et al., 2014). Digital platforms provide and contribute to information and communication in unexpected ways. The acceptance and adoption of information and communication technologies, such as Twitter, has transformed human interactions in many ways. Today, much text and other media contain embedded Twitter posts, known as tweets. The introduction of digital platforms, such as Twitter and Facebook, has caused shifts in norms of communication. Understanding this manifestation and its implications for business requires examining associated emergent phenomena. The use of “traditional” followership in this paper refers to followership without the use of modern digital platforms, such as Twitter. This study focuses on the phenomenon of followership on one platform, i.e., Twitter, and explores and ideates the phenomenon of Twitter followership.
Millions of people around the world use Twitter daily (Murthy, 2018). The Twitter environment enables users to make text-based posts, known as tweets. Users can embed tweets with content, such as pictures, videos, and cards. Twitter’s architecture and infrastructure enable social networking for connecting and building individual networks and social relations. On Twitter, users can engage in behaviors beyond tweeting, such as retweeting, hashtagging, liking, and following. Following is an important behavior and a way to establish relationships. Twitter followers can see tweets from those whom they follow. Twitter users, both individuals and companies, can follow and be followed. Thus, a bidirectional relationship (e.g., friendship) or unidirectional relationship (e.g., followership) can exist between followers and those followed. These relationships contribute to the spread of information, cooperation between entities, and influence entities (Charron, et al., 2006; Freberg, et al., 2011; Howe, 2016). The Twitter followership phenomenon consists of users who post tweets, follow, and have followers. If followership exists, there must also be leadership; therefore, the assumption is that the processes of followership and leadership coexist on Twitter. Twitter, the company, itself, distinguishes between leaders and followers. Twitter refers to leaders as authorities while referring to followers as hubs (Gupta, et al., 2013).
Social media platforms have profound implications on people and society. The influence of modern social media differs from the leader-centric influence of the past. The advent of digital platforms, such as Twitter, has changed the dynamics of interactions between people and, subsequently, followership. The interactions and followership on Twitter differ from those found on traditional media (e.g., offices, universities, and television). Katz and Lazersfeld (1955) explained the two-step flow of information in mass media. According to the two-step flow theory, opinion leaders receive information from traditional mass media first, and then they spread this information amongst their followers. In elaborating on the two-step flow theory, Edward Shils (Shils in Pooley, 2006) posited that followers prefer interpersonal sources of information to mass media sources. Twitter followers are also unique in that they do not have an explicitly lower status than their social media influencers/leaders. An understanding of the followership phenomenon on Twitter will allow influencers to better interact with followers in their efforts to market products for businesses.
In general, management researchers have been at the forefront of followership research. A review of the extant literature indicated that Twitter followership is a little-studied subject in information systems (IS) research. Followership and followers have new definitions and meanings on Twitter. For example, being a Twitter follower does not have a negative connotation. Followership is an appropriate perspective for examining the Twitter phenomenon, in which the dominant paradigm consists of those followed by, followers, and following. In contrast, the paradigm is not dictated by those led by, leader, and leading. This basic insight indicates the indispensability of followership to Twitter.
Businesses have had a growing desire to understand social media influencers/leaders and followers. We explored opinion leadership theories; however, our interest was in understanding followers. Opinion leadership is relevant for understanding influencers. Also, we explored both Hall’s (1980) conceptualization of how messages are encoded and decoded and the application of the encoding/decoding model to participants’ understanding of Facebook’s operational logic and spatial characteristics (Ridell and Saariketo, 2015). Rather than focusing on messaging, itself, or the technology artifact, Twitter, our interest was in understanding followers on Twitter. To date, only the management literature includes followership research. Uhl-Bien, et al. (2014) established the importance of followership, noting that leadership “cannot be fully understood without considering how followers and followership contribute to (or detract from) the leadership process” [1]. Of interest to this study are the role-based lenses in understanding followership on Twitter. According to Uhl-Bien, et al. (2014), “Followership is the characteristics, behaviors and processes of individuals acting in relation to leaders” [2]. In the role-based lens, followership is a role played by individuals occupying a formal or informal position or rank (Katz and Kahn, 1978; Uhl-Bien, et al., 2014). Role-based followership focuses on how followers influence a leader’s attitudes, behaviors, and outcomes. Followers are causal agents in role-based followership (Uhl-Bien, et al., 2014). Followership consists of individual role players who have characteristics and exhibit behaviors. Followership characteristics can be follower traits (e.g., political skill), motivations (e.g., power orientation), perceptions, and constructions (e.g., followership identity). Follower behaviors can include behaviors such as voice, proactive activities, dissent, and advising. In the present study, drawing upon Uhl-Bien, et al.’s (2014) role-based lenses, the codes for comments from focus groups were categorized as follower characteristics and follower behaviors. These role-based lenses were explored to conceptualize Twitter followership.
The present research brings followership to the forefront as an important research perspective in IS. The paper is structured as follows. First, we provide a summary of the extant literature on traditional followership and Twitter followership. Next, there is a presentation of the methods used to study Twitter followership, followed by the findings and a discussion. At the end, the paper presents the limitations of our research, opportunities for future work, and conclusions. A companion paper focuses on the relationships between Twitter influencers and their followers through an extensive analysis of millions of tweets with IBM Watson.
Early followership literature focused primarily on leaders; furthermore, followership literature was contextualized to organizations. Contemporary followership literature has led to a renewed interest in followership with a focus on followers (Bligh, 2011; Kelley, 1988). The limited amount of literature has provided some perspectives on followership and definitions of followers.
Leader-centric followership
In the earliest followership study, Barnard (1938) theorized cooperation and organization by studying the functions and methods of executives in formal organizations. He described the leader-follower relationship as an employer-employee dynamic, in which followers engage in supporting the mission and the leader and are independent actors with self-interests.
Burns (1978) introduced the followership concept and upended the typical transactional view of the past with a relational leadership approach. In the relational view of leadership, Burns transcended followers from entities engaged in transactions and buyer-seller exchange. In discussing the conscious choice of both leaders and followers to work and grow, Burns considered followers’ choice and described follower power, a concept absent in prior literature.
Hersey and Blanchard (1977, 1969) and Fiedler (1971, 1964) supported the idea of follower power. According to these scholars, leaders adjust their leadership styles based on the situational needs of the environment and followers. Followers may even orchestrate the situation. In fact, Greenleaf (1977, 1970) presented leaders as servants, with followers having power.
To further understand leader and follower roles, it is instructive to examine the relationship between the locus of power and the nature of work. Heifetz (1994) described adaptive work and distinguished the work done by organizational leaders as technical fixes and adaptation. The nature of the work varies for technical fixes and adaptation. Unlike technical fixes, adaptive work presents a dilemma. Adaptive work has problems that require learning; thus, the locus of work shifts to the stakeholders, and work becomes experimental and risky (Heifetz, 2010).
Based on the nature of work, Heifetz (2010) challenged traditional leader-follower relationships. In the traditional sense, work is for technical fixes, with clear solutions; therefore, the locus of work exists with authority, and work is optimized for execution. With adaptive work, solutions exist in the stakeholders’ collective intelligence at all organizational levels. An organization addressing adaptive work requires changed values, beliefs, and/or behaviors (Heifetz, 1994). In other words, adaptive work requires changes in the followers’ and followership’s values, beliefs, and/or behaviors. Adaptive work is a strong rationale for the contemporary concept of followership as it focuses on the power of followers and followership.
Contemporary followership
Whereas prior followership literature has focused on leaders, contemporary followership literature has focused on followers. Zaleznik (1965), Kelley (1988), Chaleff (1995), and Kellerman (2008) developed the contemporary followership theory. In 1988, Kelley published his essay “In praise of followers,” bringing followership and followers to the mainstream and garnering a great deal of attention (Baker, 2007). Zaleznik focused on followers before Kelley and theorized about followers’ roles in subordinacy and behavioral patterns. Zaleznik developed his ideas from a Freudian perspective, which contemporary academics have regarded as outdated due to its psychodynamic inner workings. Kelley framed followers with independence and engagement (Baker, 2007; Keim, 2013). Chaleff (1995) expanded on the literature and described courageous followers standing up to and supporting leaders. Kelley and Chaleff paved the way for contemporary followership theories; their works have resulted in discussions and followership research (Baker, 2007; Keim, 2013). Kellerman (2008) further expanded on the literature and indicated effective follower engagement and the notion of good and bad followers as a value judgment. Of importance, Kellerman looked to history and proposed the ongoing and imminent nature of a power shift from leaders to followers due to changes in culture and technology. Kellerman explained the power shifts in patterns of engagement, dominance, and deference that exist among followers and leaders.
Twitter followership
Followership is an important aspect of digital platforms such as Twitter. Digital platforms enable the contexts and manifestations of followership phenomena.
Followership is the ontology, the very nature of Twitter’s existence. Twitter exists primarily as a means of facilitating followership, a phenomenon the platform has produced. Thus, understanding digital platforms, such as Twitter, requires understanding the followership associated with them. The contemporary followership literature described earlier suggested the complex and multidimensional nature of followership. By extension, this study indicates the equally complex and multidimensional nature of Twitter followership.
This study is based on the premise that Twitter followership differs from organizational followership. Unlike in organizations, information technology (IT) of digital platforms enables networks of followers, and followers are not employees or subordinates. Twitter followers are geographically dispersed and location-independent users. Twitter followers participate proactively and act with tweets or other behaviors enabled by Twitter in real-time.
In traditional followership without a digital platform, a person might physically follow and physically interact with leaders. For example, a follower of political candidates might attend their speeches and rallies. Followers might consume media to view, listen to, and read about these candidates. The consumption of media causes followers to become viewers, listeners, readers, and subscribers.
On the other hand, follower power is the essence of Twitter that enables its very existence. Power indicates agency and cause and effect. Twitter enables the phenomenon of following without the limiting aspects of traditional followership, such as physical proximity. Twitter provides radical novelty, as digital platforms “fulfill a given function by using a different basic principle as compared to what was used before to achieve a similar purpose” [3]. People can use digital platforms to follow others, anywhere and anytime (Leonardi and Vaast, 2017).
This study employed focus groups and qualitative analyses to generate insights into Twitter followership phenomenon. The focus group discussions were recorded and then transcribed with consent from all of the participants. The transcribed text — the qualitative data — was analyzed using two methods. Multiple approaches exist for analyzing qualitative data from focus group discussions (Rabiee, 2004); therefore, there is no universal approach for analyzing qualitative data (Onwuegbuzie, et al., 2009). The first analysis was conducted using the narrative method. It enabled an exploration of the Twitter followership process and an assessment of its foundational propositions that are often assumed to be true without verification. The second analysis was conducted using the framework method. This second analysis enabled the discovery of the key Twitter followership constructs. All methods employed passed the Institutional Review Board review, and they received exempt status.
Focus groups are an ideal method for data collection of unexplored domains (Edmunds, 1999). Twitter followership is a new and unexplored phenomenon afforded by new technology. Focus groups allow us to peer into the Twitter-human augmentation. As noted earlier, scant literature exists on Twitter followership; therefore, our research focused on the firsthand experiences of Twitter users to understand the phenomenon. Focus groups are best suited for collecting data from hands-on users (Carey and Asbury, 2012). Focus groups enable collecting rich and detailed data because participants offer candid responses (Krueger and Casey, 2009). Focus groups are group processes in which participants explore and clarify their views, leading to a superior understanding of the domain and the underlying constructs within it.
Data collection took place in three focus group discussions at a university in the southeastern part of the United States in 2018. Each group discussion was approximately 90 minutes long. The target population consisted of Twitter users knowledgeable about the platform so that they could provide rich information. Craigslist and Facebook ads, fliers on public community boards, e-mail messages to undergraduate and graduate students, and solicitation on personal networks were the means of recruitment. All prospective participants filled out a screening questionnaire of their active use of Twitter and their willingness to attend a focus group discussion at a specific time and date. Those interested in and qualified to participate received a second invitation with confirmed attendance for given times. Successful recruitment occurred for 19 focus group participants. According to Krueger and Casey (2009), the typical focus group size is five to eight people. Our focus groups were within the normal size range. The details on each focus group size and demography can be found in Table 1.
Open-ended interview questions were used to prompt and guide the focus group participants (see Appendix A). Three doctoral students acted as moderators and facilitators by asking questions, managing the operations, and assisting with the technical aspects of running the focus groups. The participants were asked about their Twitter usage, Twitter’s social and relational dynamics, and personal characteristics and behaviors.
Table 1: Focus group size and demography. Focus group n Gender Age Employment Marital status Recruitment 1 7 Female: 6
Male: 118–24: 3
25–34: 1
34–44: 3Full-time: 3
Self-employed: 2
Student: 2Single: 5
Married: 1
Divorced: 1Craigslist: 1
Facebook: 4
Flyer: 1
Referral: 12 6 Female: 4
Male: 218–24: 3
34–44: 1
55–64: 2Full-time: 1
Part-time: 1
Student: 2
Unemployed: 2Single: 4
Married: 1
Divorced: 1Craigslist: 2
Facebook: 3
Twitter: 13 6 Female: 4
Male: 218–24: 3
25–34: 3Full-time: 2
Part-time: 2
Student: 1
Unemployed: 1Single: 5
Married: 1Craigslist: 3
Facebook: 2
Flyer: 1Total 19 Female: 14
Male: 518–24: 9
25–34: 4
34–44: 4
45–54: 0
55–64: 2Full-time: 6
Part-time: 3
Self-employed: 2
Student: 5
Unemployed: 3Single: 14
Married: 3
Divorced: 2Craigslist: 6
Facebook: 9
Twitter: 1
Flyer: 2
Referral: 1
Analysis #1: Narratives
To understand Twitter followership, we conceptualize it based on narratives (i.e., stories) of Twitter users. A qualitative analysis of narratives is an appropriate approach for macro-level phenomena (Riessman, 2002). It consists of analyzing a narrative (Earthy and Cronin, 2008; Riessman, 2002). According to Earthy and Cronin (2008), people in groups engage in storytelling, so produce narratives of their lives in the process. According to Rosenwald and Ochberg (1992), social construction and personal stories go beyond telling someone or oneself about one’s life, as they are the ways by which identities can be fashioned. In this study, the focus group discussions consisted of stories of how Twitter users constructed their Twitter identities and followership. We identify the entities in narratives and plots (i.e., processes in relation to Twitter).
Analysis #2: Constructs
The focus group discussion data underwent further analysis with the framework method. The framework analysis method has seven stages (Gale, et al., 2013). Figure 1 shows the seven stages of the framework method.
Figure 1: Seven stages of the framework method.
After transcription, qualitative analysis entailed reading and listening to focus group recordings for familiarization. The third stage of the framework method required reading and coding the transcripts line by line. Dedoose, a qualitative data analysis software available online, was the means used to code and analyze the transcripts.
This study did not include developing a new framework; instead, we used an existing framework from the extant literature. The role-based lens was our analytical framework because it is a relevant and highly applicable approach for the context under study. According to Uhl-Bien, et al. (2014), followership is the characteristics, behaviors, and processes of individuals. In the role-based lens, followership is a role played by individuals occupying a formal or informal position or rank (Katz and Kahn, 1978; Uhl-Bien, et al., 2014). Role-based followership focuses on how followers influence a leader’s attitudes, behaviors, and outcomes. Followers are causal agents in role-based followership (Uhl-Bien, et al., 2014). Followership consists of individual role players who have characteristics and exhibit behaviors. Followership characteristics can be follower traits (e.g., political skill), motivations (e.g., power orientation), perceptions, and constructions (e.g., followership identity). Follower behaviors can include behaviors such as voice, proactive activities, dissent, and advising. In our study, the codes were categorized as follower characteristics and follower behaviors. The synthesis and categorization of the codes from stage 3 in Figure 1 resulted in the identification of Twitter follower constructs.
Twitter followership narratives
The Twitter narratives had entities with distinct identities and acts. Figure 2 illustrates the entities — follower, leader/influencer, and Twitter. The narratives of Twitter users showed a conceptualization of Twitter followership (see Figure 2). The dashed lines in Figure 2 indicate traditional followership acts, while the solid lines show Twitter followership acts. Twitter (i.e., a social media platform) facilitates leader-follower interaction, and the narratives support this notion. This interaction involved self-representation by the users and relational dynamics determined by Twitter. The inclusion of Twitter in Figure 2 is a fundamental distinction. Twitter shapes individuals’ self-identities. The dominant components of a leader-follower interaction are described next.
Figure 2: Twitter leader and follower entities and acts.
Leadership and followership are established concepts. Drawing from the extant literature on these concepts, we consider the five foundational propositions essential for extending traditional leadership and followership concepts to Twitter phenomenon. Figure 2 shows the positions of followers, leaders/influencers, and Twitter in leader-follower interactions. Twitter users engage in self-representation, influenced by the relational and social dynamics of the system. Twitter users’ narratives include their descriptions of self-representation and the enactment of symbolic behaviors. We discovered that users remain attentive to their use of Twitter while constructing themselves. Twitter shaped how users self-represent on the platform. A focus group participant explained the difficulty with self-expression and its construction within the confines of Twitter:
You never realize how creative you can be until you’re only given 140 characters. You never know how easily you can say something until you have a limit. I need to get this out, but I want to use this platform to say it. So, how am I going to say it? In another narrative, a participant discussed engaging in self-representation on Twitter based on affective intentions. The participant considered the impact of their self-expression on potential followers on the receiving end, stating:
I’ll put or share things about nature that are pretty. I try to do positive things or nothing. I like a lot of humor on there, too. That’s what I decided. Nothing that’s gonna hurt anybody. I don’t like to say things that are confrontational. I don’t like to get into fights on there at all. So, I don’t put anything confrontational on there. Twitter has resulted in the creation and partitioning of its users into leader-follower interactions with relational and social dynamics. Interactions can sometimes occur outside of Twitter, as shown by the dashed line in Figure 2. Based on the narratives collected from our focus groups, when interactions originate on Twitter, users continue engaging in their interactions on Twitter. It is possible that followers could read a tweet and post about it on another platform such as Instagram or share it with a friend in person. However, this was not common or evident in the focus group discussions.
Twitter enables relational and social dynamics, and the interactions differ from interactions in traditional contexts. As a result, we were able to develop five propositions by applying the traditional followership theory to the new and divergent context of Twitter followership, with the narratives providing evidence for the propositions.
Proposition 1. The process of followership/leadership is present on Twitter
The focus group participants described how Twitter users engage in following other Twitter users in their narratives. If the act of following occurs, the act of leading is an inevitable occurrence. Although it is a natural consequence of the Twitter platform, the magnitude of followership and its ramifications are enormous. The focus group narratives provided ample support for this proposition. One participant stated:
I basically follow anyone who follows me. I [think], “Oh. They follow me. I’ll follow back.” I don’t think about it. But if I go out and choose to follow someone, it’s probably someone like a celebrity [I] like. If I meet somebody, I [ask], “Hey. What’s your Twitter? Do you have a Twitter?’ I add them. If I decide to unfollow somebody or if I just don’t follow them, it’s because I maybe can’t relate to them. They’re not posting relatable content. If I notice that there’s some weird stuff on my timeline, I [think], “Oh, no. Let me hit ‘unfollow’.” But yeah, that’s about it. I’m not really picky with my followers and followings. Proposition 2. Twitter leader-follower interaction is ongoing
The focus group participants provided narratives of ongoing leader-follower interactions. Their interactions are not one-time events; rather, they are continuous and build on previous interactions. A focus group participant described ongoing Twitter interactions:
Now [and then], I will look up people [whom] I don’t necessarily agree with. But politically, I flatly refuse to follow a 45. I will not give him the justification [by following his profile], but I want to stay abreast of views that are not necessarily my own because I need to see what these yahoos out here are saying. I don’t want just a one-sided view of my world — everybody [who] agrees with me. I want there to be diversity. The participant referred to the 45th U.S. President as 45 and stated that she refused to follow him but strived to keep up with the views of others in the interest of diversity of thought. The participant maintained the leader-follower interaction even when not agreeing with and contradicting the leader. Thus, the leader-follower interaction has taken a new form. The leader-follower interaction is not bound by the exchange of common values seen in traditional leader-follower interactions. The participant appears to be engaged for the sake of an ideal — an ultimate standard. Furthermore, the maintenance and continuity of the leader-follower interaction does not appear to have a significant cost to the participants.
Proposition 3. Followers have power
Followers have the power to influence. One focus group participant described her interaction with a follower who challenged her and influenced her after a tweet:
I have shared something, and someone was not aware of [it], and so then they may react to that and delve into it for more information. I have actually seen [that] they come back to me and say, “Hey, well, this article wasn’t particularly correct,” or not that it wasn’t correct, but [it] wasn’t completely forthcoming, and so here’s some other details. So, I [have] noticed that people have challenged me on things, and I actually appreciate that. Followers power appears to be a new creation or an amplification by the platform. The participant (leader) described her ongoing leader-follower interactions where she was able to influence, resulting in a reaction by her followers who challenged her statements. Her expressions were influencing the followers who reacted and challenged; thus, the followers have power. This is not a unique occurrence, and many more participants shared similar experiences with follower power.
Proposition 4. Twitter followers are co-creators of Twitter leadership/followership
Followers’ words have an influence. The focus group participants’ narratives showed that they were both followers and cocreators as Twitter users. A focus group participant described the sense of accomplishment that she felt as a cocreator:
When I see a retweet or someone asks me for something on Twitter, it’s refreshing. It’s like, oh, yeah! They’re taking my opinion or something into consideration, and they validate me by liking what I like verbatim. They didn’t even take the time to change what I said into their words. They just took my words exactly for how they felt. So, I think it is influential in a way. In having power, followers appear to be able to create the social fabric with their words. Followers’ expressions matter. They are not extinguished, neglected, or transformed in favor of the leaders’ expressions. Follower’s opinions are considered by other Twitter users. Her words, which are her creations, were retweeted and spread without alteration.
Proposition 5. Twitter followers take on unique and important roles in the act of leadership/followership
Users’ roles on Twitter are evident in the narratives. Twitter users exhibit a variety of characteristics and behaviors in their roles. Participants did not describe a standard for their Twitter roles. A focus group participant described Twitter characteristics and behaviors as aggressive or passive and said:
Twitter is a great way to have an ego about yourself. So, if you want to be known as someone more aggressive, you can have that ego by being aggressive. In this case, the role of “aggressive” appears to be an expression of the participant’s self-represented identity. But different users may take on different roles and even changing roles. Some participants noted that Twitter caused them to alter their normal social behaviors and explained behavioral and role shifts. A focus group participant described these shifts, stating:
I’m a pretty talkative person. But, on Twitter, I’m not that talkative because I don’t make personal posts. I do a lot of retweeting. I do post every now and then — just something. Some focus group participants played a role in which they confronted and directly addressed issues. A participant described using Twitter to draw attention to an issue:
I was at Walmart one day, and literally, there was a guy in front of me, and he was just trying to load money on a prepaid card. All of a sudden, these loss-prevention officers just swarmed him. They took a photo of his ID and his debit card. And, I was like, “What the hell, Walmart!” I was on Twitter. I will definitely speak out about that type of thing. If they know what’s good for them, they will respond quickly. And they generally do. Theoretically, Twitter users could exist without having explicitly listed followers; however, this is an unlikely occurrence that did not present itself in our narratives. Moreover, Twitter users simultaneously take on follower and leader roles. It was a challenge in this study to decipher or clearly find differences between these roles in the narratives. Some of the focus group participants described themselves as followers but also as those having followers.
Twitter followership constructs
As described (see Figure 1, Stage 5), framework analysis of the focus group data was conducted to develop constructs of Twitter followers. The charting of the codes occurred in the framework matrices (see Tables 2 and 3). Using the analytical framework of the role-based lens (Uhl-Bien, et al., 2014) as a guide, the codes were grouped naturally under two categories: followers’ characteristics and behaviors. Multiple coders were involved in the coding process. The initial coding had an interrater reliability of 72 percent. After discussion and agreement, the interrater reliability increased to 92 percent.
Fifty codes emerged from the data. Appendix B shows these codes and their frequency counts. A careful categorization of the codes resulted in the identification of the following constructs: sense of power, eCourage, social capital, voice, help, empowerment, and disempowerment. Of these constructs, sense of power, eCourage, and social capital are follower characteristics (see Table 2); voicing, helping, empowering, and disempowering are follower behaviors (see Table 3).
Table 2: Categories of follower characteristics with codes. Sense of power eCourage Social capital Current events
Judgment
Snooping
Functionality
Options
Follow-upSocial activism
Anonymity
Privacy
Filter/no filter
Confrontation
FearFollowers
Friends
Family
Keeping in touch
Familiar
Network
Pressure
Relevance
Bond
Follower characteristics
Follower characteristics are a component of the role-based lens (Uhl-Bien, et al., 2014). Follower characteristics have a direct impact on follower enactment and are the very definition of followership. Traditional followership literature has described the vast and varied nature of follower characteristics, which include follower traits (e.g., goal orientation and analytical skills), motivations (e.g., power orientation), and perceptions and constructions (e.g., follower identity and implicit followership). Our framework analysis produced three constructs for Twitter follower characteristics: sense of power, eCourage, and social capital.
Followers exhibit a sense of power. Twitter users have self-held beliefs about their power and the ability to influence other people on the platform. Twitter provides its users with a sense of power that allows them to access information, exercise personal judgment, and stay up to date. Unlike traditional followership contexts, Twitter followers can independently rationalize and engage in decision-making.
Twitter users have courage. We call it eCourage. Twitter users exhibit a willingness to act in spite of fear or consequences. According to Chaleff (1995), individuals are responsible for their actions whether they follow or lead; as such, it takes courage to act. However, the concept of eCourage differs from traditional courage as eCourage is a trait enabled and facilitated by the platform. Traditional courage exists in multiple forms and with multiple definitions. For example, Woodard and Pury (2007) typified traditional courage into four categories: (1) work/employment courage; (2) patriotic, religion, or belief-based physical courage; (3) social–moral courage; and, (4) independent courage or family-based courage. In this vein, eCourage is a type of courage, and it materializes in the context of platforms such as Twitter. Twitter offers anonymity and other features providing conditions in which people have freedom of expression and can speak their mind. However, users are susceptible to consequences of the Twitter-enabled mechanisms for relational and social dynamics, even if the users maintain anonymity. For example, anonymous users can be banned from Twitter by moderators. In some cases, Twitter users do make their personal information (e.g., full name and place of employment) public and voice their opinions. This may result in retribution from the community.
Twitter users also carry and generate social capital. Social capital differs by individuals. Some users naturally possess social capital because of their personal networks, while others develop social capital on the platform. In any case, most users increase their social capital with increased Twitter use.
Follower behaviors
Behaviors are a component of the role-based lens (Uhl-Bien, et al., 2014). Follower behaviors are actions in which individuals engage to enact their follower roles. The framework analysis of focus group data showed that Twitter users’ role-based behaviors are not necessarily required or expected of Twitter users. Rather, they are unexpected or unrequired behaviors, otherwise known as extra-role behaviors (Van Dyne and LePine, 1998). In fact, Twitter users do not have explicit or defined roles, as in traditional followership instances (e.g., in company jobs). Twitter followers independently and voluntarily take on extra-role behaviors and engage in voicing, helping, empowering, and disempowering behaviors (see Table 3).
Twitter users take many verbal actions, which we labeled as voicing behaviors. These include espousing views, sharing opinions, engaging in conflict, challenging leaders, venting about issues, and objecting to presented ideas. Twitter users also engage in helping behaviors to assist their followers and, in some cases, leaders. Helping behaviors include entertaining, affiliating, teaching, confirming, validating, tagging, and defending.
Table 3: Categories of follower behaviors with codes. Voicing Helping Empowering Disempowering Espousing
Opining
Conflicting
Challenging
Venting
ObjectingEspousing
Entertaining
Affiliating
Teaching
Confirming
Validating
Tagging
DefendingFollowing
Retweeting
Liking
Sharing
Incentivizing
Endorsing
Advocating
Motivating
AffirmingUnfollowing
Avoiding
Ignoring
Blocking
Trolling
Cyberbullying
Trash-talking
Twitter users either engage with or disengage from leaders to empower or disempower their leaders. Clearly, Twitter users who engage in the followership process engage in both empowering and disempowering behaviors. Empowering and disempowering are antithetical behaviors; however, users do not enact these behaviors in equivalent and opposite ways. Empowering behaviors consist of increasing the power of leaders by following, retweeting, liking, and sharing. Disempowering behaviors decrease leaders’ power by exercising dismissive actions. Specifically, Twitter users engage in disempowering behaviors by unfollowing, avoiding, and ignoring.
Our findings do not suggest that these are the only characteristics and behaviors of Twitter users; however, they are the ones that emerged from data and analysis with the framework method. In this sense, our results are preliminary in this yet unexplored domain.
Followership research is limited. In contrast, leadership receives more weight in many traditional contexts. There may be a justified reason for the significant interest in leadership research in traditional followership contexts. However, the world has changed due to the digital revolution and social media. Similar to the introduction of Gutenberg’s printing press, the introduction of digital platforms has resulted in the transformation of human evolution, human interaction, and followership. Some traditional followership concepts have dissolved due to Twitter followership. For example, as proposed in the great man theory of leadership, the idea of good leaders being born with innate leadership traits has declined in popularity. In some cases, leaders have obliviated and reemerged as influencers; this shift extends beyond semantics.
Leaders select followers in traditional leadership, giving followers opportunities to interact with leaders. In contrast, followers can engage in the selection of leaders in Twitter followership. Followers can give leaders the opportunities to interact with them. This seemingly little difference in initiation has significant large-scale implications. In a traditional context, followers are offered leaders (e.g., employers), and they choose from the offerings. An employer typically selects the employee, and the employee must select one of the employers made available to them. In Twitter followership, followers can offer to follow, making the first move in the interaction. Therefore, Twitter followers have an inherent advantage in their interactions with their leaders. Such a critical distinction has produced unique findings in our research.
Traditional followership research, by extension, may provide some insights into Twitter followership. An apparent link between Twitter followership and traditional followership exists, as Twitter users can engage in or at least have the option of engaging in traditional followership with off-Twitter interactions. However, while there may be some similarities between the two, leaders/influencers and followers are not the same concepts in traditional and Twitter followership.
This research conceptualizes Twitter leader and follower entities and acts (see Figure 2). The narratives provided rich accounts with details about Twitter followership. We also examined the role of Twitter users by investigating the users’ role-based characteristics and behaviors. In extant literature, there are many follower characteristics (e.g., political skill, goal orientation, Machiavellianism, mission consciousness, motivation to lead, power orientation, role orientations, romance of leadership, and followership identity) (Uhl-Bien, et al., 2014). As for behaviors, some of those we found in extant literature included proactive behavior, initiative taking, obedience, resistance, upward influence, voice, dissent, feedback seeking, and advising (Uhl-Bien, et al., 2014). These characteristics and behaviors were mostly from organizational studies. We were able to extend and develop users’ characteristics and behaviors specific to Twitter.
Social media has emerged as a preeminent source of information for many millennials, Gen Z, and other groups. Influencers, who often receive compensation from corporate entities, exist because numerous product discussions take place on social media. This research enabled us to provide social media influencers and businesses with a general idea of how interactions occur on Twitter (see Figure 2). Influencers and businesses can use the constructs identified in this study to understand their Twitter followers, based on specific characteristics and what they want to be or do, based on the noted behaviors. The three characteristics and four behaviors recognized in this study can be used to profile and target various customer groups. Twitter user characteristics and behaviors can be used to observe behaviors in a customer base of influencers and businesses. That is, the repertoire of identified Twitter behaviors provides guidance for influencers and businesses on what to expect from a customer base on Twitter as well as suggest how a customer base on Twitter could potentially react.
The literature on traditional followership and leadership contains many views of followers and followership, including the leader-centric, follower-centric, relational, role-based, and constructionist views (Uhl-Bien, et al., 2014). In this study, the ideation of Twitter followership draws upon and is limited to a role-based view. Also, there are many conceptualizations regarding followers and followership in theories, such as the great man, situational leadership, leader-member exchange, and courageous followership theories. Our goal was to ideate the Twitter followership phenomenon, not to develop theory.
IT-based followership platforms are here to stay. Thus, from a practical and industry perspective, a deeper understanding of how they work can only improve business and societal communication and productivity. In many ways, IT-enabled followership is a new kind of leadership/followership. Platforms such as Twitter enable what appears to be new forms of preaching, selling, and king-making. This has direct implications for influencers in marketing products for businesses on Twitter. The conflation of traditional and new leadership/followership, such as Twitter followership, creates challenges and opportunities in unexpected ways. Organizations and institutions should consider our findings to understand the current Twitter phenomenon for business purposes.
Followership research in IS is an unexplored territory. Nevertheless, it is vital to engage in this line of research, as IT provides new and nuanced ways for leaders and followers to interact, as evidenced by our study. Researchers in the future are called to further examine IT-based followership using constructs and theories from traditional followership.
About the authors
Vishal Uppala is Assistant Professor in the Department of Accounting and Information Systems at North Dakota State University.
E-mail: Vishal [dot] Uppala [at] ndsu [dot] eduPrashant Palvia is Joe Rosenthal Excellence Professor in the Bryan School of Business and Economics at the University of North Carolina at Greensboro.
E-mail: pcpalvia [at] uncg [dot] eduKalyani Ankem is Associate Professor in the Department of Business Informatics at Northern Kentucky University.
E-mail: ankemk1 [at] nku [dot] edu
Notes
1. Uhl-Bien, et al., 2014, p. 89.
2. Uhl-Bien, et al., 2014, p. 97.
3. Rotolo, et al., 2015, p. 1,827.
References
Deanna J. Attai, Diane M. Radford, and Michael S. Cowher, 2016. “Tweeting the meeting: Twitter use at the American Society of Breast Surgeons annual meeting 2013–2016,” Annals of Surgical Oncology, volume 23, number 10, pp. 3,418–3,422.
doi: https://doi.org/10.1245/s10434-016-5406-x, accessed 27 February 2023.Susan D. Baker, 2007. “Followership: The theoretical foundation of a contemporary construct,” Journal of Leadership & Organizational Studies, volume 14, number 1, pp. 50–60.
doi: https://doi.org/10.1177/0002831207304343, accessed 27 February 2023.Chester I. Barnard, 1938. The functions of the executive. Cambridge, Mass.: Harvard University Press.
Michelle C. Bligh, 2011. “Followership and follower-centred approaches,” In: Alan Bryman, David Collinson, Keith Grint, Brad Jackson, and Mary Uhl-Bien (editors). Sage handbook of leadership. Thousand Oaks, Calif.: Sage, pp. 425–436.
James MacGregor Burns, 1978. Leadership. New York: Harper & Row.
Martha Ann Carey and Jo-Ellen Asbury, 2012. Focus group research. New York: Routledge.
doi: https://doi.org/10.4324/9781315428376, accessed 27 February 2023.Ira Chaleff, 1995. The courageous follower: Standing up to and for our leaders. San Francisco: Berrett-Koehler Publishers.
Chris Charron, Jaap Favier, and Charlene Li, 2006. “Social computing: How networks erode institutional power, and what to do about it,” Forrester Customer Report (13 February), at https://www.cisco.com/web/offer/socialcomputing/SocialComputingBigIdea.pdf, accessed 28 February 2023.
Sarah Earthy and Ann Cronin, 2008. “Narrative analysis,” In: Nigel Gilbert (editor). Researching social life. Third edition. Los Angeles, Calif.: Sage, pp. 420–439.
Holly Edmunds, 1999. The focus group research handbook. Lincolnwood, Ill.: NTC Business Books.
Fred E. Fiedler, 1971. “Validation and extension of the contingency model of leadership effectiveness: A review of empirical findings,” Psychological Bulletin, volume 76, number 2, pp. 128–148.
doi: https://doi.org/10.1037/h0031454, accessed 27 February 2023.Fred E. Fiedler, 1964. “A contingency model of leadership effectiveness,” Advances in Experimental Social Psychology, volume 1, pp. 149–190.
doi: https://doi.org/10.1016/S0065-2601(08)60051-9, accessed 27 February 2023.Karen Freberg, Kristin Graham, Karen McGaughey, and Laura A. Freberg, 2011. “Who are the social media influencers? A study of public perceptions of personality,” Public Relations Review, volume 37, number 1, pp. 90–92.
doi: https://doi.org/10.1016/j.pubrev.2010.11.001, accessed 27 February 2023.Nicola K. Gale, Gemma Heath, Elaine Cameron, Sabina Rashid, and Sabi Redwood, 2013. “Using the framework method for the analysis of qualitative data in multi-disciplinary health research,” BMC Medical Research Methodology, volume 13, article number 117.
doi: https://doi.org/10.1186/1471-2288-13-117, accessed 27 February 2023.David Garcia, Pavlin Mavrodiev, DanieleCasati, and Frank Schweitzer, 2017. “Understanding popularity, reputation, and social influence in the Twitter society,” Policy & Internet, volume 9, number 3, pp. 343–364.
doi: https://doi.org/10.1002/poi3.151, accessed 27 February 2023.Robert K. Greenleaf, 1977. Servant leadership: A journey into the nature of legitimate power and greatness. New York: Paulist Press.
Robert K. Greenleaf, 1970. The servant as leader. South Orange, N.J.: Greenleaf Center for Servant Leadership, Seton Hall University.
Pankaj Gupta, Ashish Goel, Jimmy Lin, Aneesh Sharma, Dong Wang, and Reza Zadeh, 2013. “WTF: The who to follow service at Twitter,” WWW ’13: Proceedings of the 22nd international conference on World Wide Web, pp. 505–514.
doi: https://doi.org/10.1145/2488388.2488433, accessed 27 February 2023.Stuart Hall, 1980. “Encoding/decoding,” In: Stuart Hall, Dorothy Hobson, Andrew Lowe, and Paul Willis (editors). Culture, media, language. Working papers in cultural studies, 1972–79. London: Routledge, pp. 128–138.
Ronald A. Heifetz, 2010. “Adaptive work,” Journal of the Kansas Leadership Center, pp. 72–77, at https://www.hesston.edu/wp-content/uploads/2017/12/KLCAdaptiveWork.pdf, accessed 1 January 2018.
Ronald A. Heifetz, 1994. Leadership without easy answers. Cambridge, Mass.: Belknap Press of Harvard University Press.
Paul Hersey and Ken H. Blanchard, 1977. Management of organizational behavior: Utilizing human resources. Third edition. Englewood Cliffs, N.J.: Prentice Hall.
Paul Hersey and Ken H. Blanchard, 1969. “Life cycle theory of leadership,” Training & Development Journal, volume 23, number 5, pp. 26–34.
Neil Howe, 2016. “Brands are under the (social) influence,” Forbes (31 March), at https://www.forbes.com/sites/neilhowe/2016/03/31/brands-are-under-the-social-influence/?sh=17f8661c5f49, accessed 1 January 2018.
Daniel Katz and Robert L. Kahn, 1978. The social psychology of organizations. Second edition. New York: Wiley.
Elihu Katz and Paul F. Lazarsfeld, 1955. Personal influence: The part played by people in the flow of mass communications. Glencoe, Ill.: Free Press.
Susan Keim, 2013. “Following the leader or leading the follower? Exploring the effects of mission-driven vs. leader-driven community participation,” doctoral dissertation, University of Kansas, at http://hdl.handle.net/1808/12934, accessed 1 January 2018.
Barbara Kellerman, 2008. Followership: How followers are creating change and changing leaders. Boston, Mass.: Harvard Business School Press.
Robert Kelley, 1988. “In praise of followers,” Harvard Business Review, volume 66, number 6, pp. 142–148, and at https://hbr.org/1988/11/in-praise-of-followers, accessed 27 February 2023.
Richard A. Krueger and Mary Anne Casey, 2009. Focus groups: A practical guide for applied research. Fourth edition. Los Angeles, Calif.: Sage.
Paul M. Leonardi and Emmanuelle Vaast, 2017. “Social media and their affordances for organizing: A review and agenda for research,” Academy of Management Annals, volume 11, number 1, pp. 150–188.
doi: https://doi.org/10.5465/annals.2015.0144, accessed 1 January 2018.Dhiraj Murthy, 2018. Twitter: Social communication in the Twitter age. Second edition. Cambridge: Polity Press.
Anthony J. Onwuegbuzie, Wendy B. Dickinson, Nancy L. Leech, and Annmarie G. Zoran, 2009. “A qualitative framework for collecting and analyzing data in focus group research,” International Journal of Qualitative Methods, volume 8, number 3, pp. 1–21.
doi: https://doi.org/10.1177/160940690900800301, accessed 27 February 2023.Jefferson Pooley, 2006. “Fifteen pages that shook the field: Personal influence, Edward Shils, and the remembered history of mass communication research,” Annals of the American Academy of Political and Social Science, volume 608, number 1, pp. 130–156.
doi: https://doi.org/10.1177/0002716206292460, accessed 27 February 2023.Fatemeh Rabiee, 2004. “Focus-group interview and data analysis,” Proceedings of the Nutrition Society, volume 63, number 4, pp. 655–660.
doi: https://doi.org/10.1079/PNS2004399, accessed 27 February 2023.Seija Ridell and Minna Saariketo, 2015. “Negotiating the architectural power of connective media. Stuart Hall’s encoding/decoding model and the critical study of digitally afforded social environments,” ISIS Summit Vienna 2015.
doi: https://doi.org/10.3390/isis-summit-vienna-2015-S3006, accessed 27 February 2023.Catherine K. Riessman, 2002. “Analysis of personal narratives,” In: Jaber F. Gubrium and James A. Holstein (editors). Handbook of interview research: Context & method. Thousand Oaks, Calif.: Sage, pp. 695–710.
George C. Rosenwald and Richard L. Ochberg (editors), 1992. Storied lives: The cultural politics of self- understanding. New Haven, Conn.: Yale University Press.
Daniele Rotolo, Diana Hicks, and Ben R. Martin, 2015. “What is an emerging technology?” Research Policy, volume 44, number 10, pp. 1,827–1,843.
doi: https://doi.org/10.1016/j.respol.2015.06.006, accessed 27 February 2023.Mary Uhl-Bien, Ronald E. Riggio, Kevin B. Lowe, and Melissa K. Carsten, 2014. “Followership theory: A review and research agenda,” Leadership Quarterly, volume 25, number 1, pp. 83–104.
doi: https://doi.org/10.1016/j.leaqua.2013.11.007, accessed 27 February 2023.Linn Van Dyne and Jeffrey A. LePine, 1998. “Helping and voice extra-role behaviors: Evidence of construct and predictive validity,” Academy of Management Journal, volume 41, number 1, pp. 108–119.
Katrin Weller, Axel Bruns, Jean Burgess, Merja Mahrt, and Cornelius Puschmann (editors), 2014. Twitter and society. New York: Peter Lang.
doi: https://doi.org/10.3726/978-1-4539-1170-9, accessed 27 February 2023.Cooper R. Woodard and Cynthia L.S. Pury, 2007. “The construct of courage: Categorization and measurement,” Consulting Psychology Journal: Practice and Research, volume 59, number 2, pp. 135–147.
doi: https://doi.org/10.1037/1065-9293.59.2.135, accessed 27 February 2023.Abraham Zaleznik, 1965. “The dynamics of subordinacy,” Harvard Business Review, volume 43, number 3, pp. 119–131.
Appendix A: Focus group discussion questions
Appendix B: List of codes and frequency counts. Code Frequency Count Code Frequency Count Current events 72 Opinionating 20 Entertaining 64 Conflicting 18 Following 56 Options 17 Social Activism 46 Pressure 15 Judgment 43 Avoiding 14 Retweeting 38 Ignoring 14 Anonymity 37 Challenging 13 Snooping 34 Teaching 11 Liking 33 Objecting 11 Affiliating 31 Venting 11 Followers 29 Blocking 10 Privacy 29 Endorsing 9 Family 27 Confirming 9 Friends 27 Validating 9 Sharing 27 Relevance 8 Keeping-in-touch 26 Tagging 8 Familiar 24 Following up 7 Filter/no filter 24 Cyberbullying 7 Functionality 23 Trolling 7 Confrontation 23 Advocating 7 Espousing 22 Motivating 7 Network 21 Affirming 6 Fear 20 Defending 6 Unfollowing 20 Bonding 5 Incentivizing 20 Trash-talking 2
Editorial history
Received 15 October 2022; revised 28 November 2022; accepted 27 February 2023.
This paper is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.Anatomy of Twitter followership
by Vishal Uppala, Prashant Palvia, and Kalyani Ankem.
First Monday, Volume 28, Number 3 - 6 March 2023
https://firstmonday.org/ojs/index.php/fm/article/download/12825/10819
doi: https://dx.doi.org/10.5210/fm.v28i3.12825
