Alternative Commentaries on the 2020 US Presidential Election

A Netnographic Approach to Audience Participation

Team Members

Daniel Jurg, Dieuwertje Luitse, Saskia Pouwels, Marc Tuters, Patrick Antwi, Nil Yüce, Clair Richards, Mariska van Schijndel, Carlijn van Esch, Andrea Pronzati.

Visualizations by Andrea Pronzati.

The presentation can be found here

Contents

Summary of Key Findings

This Digital Methods Winter School project looked at the way that audiences engaged with “alternative influencers” during the 2020 U.S. Presidential Election. Mapping the participatory practices of audiences during live streams of HasanAbi, The Young Turks, The David Pakman Show, and Steven Crowder on Election Night, this exploratory study found that:

1. The majority of HasanAbi ’s audience on Twitch is driven by Hasan’s authentic live performance, formulating political ideologies and commentary on social and political events during hours-long live streams. The interaction between thousands of community members and Hasan seems to be based on a common subcultural practice and understanding of specific vernacular and the repetitive use of unique emotes.

2. On YouTube, the established progressive channel The Young Turks attracted vast numbers of pro-Trump supporters who, as part of their shared online experience, were looking for another liberal meltdown -- a reference back to the TYT responses to the results of the 2016 U.S. Presidential Election. In contrast, the rising progressive channel The David Pakman Show revealed a supportive progressive community characterized by intimate audience relations founded on political alignment.

3. Perhaps counterintuitive, by observing the audiences of the conservative influencer Steven Crowder on his alternative platform BlazeTV, our findings suggest that — at least for now — the participatory, and playful, infrastructures afforded by mainstream platforms such as YouTube and Twitch create a more intimate media ecosystem rather than in a “closed-off” alternative platform.

As an overarching observation, the speed and ephemerality of the live streams on YouTube and Twitch made the dominant mode of communication in the chats iconographic. This exploratory project, therefore, directed most of its attention to this visual aspect and how these icons accumulated meaning within the broader discourse. Figure 1 presents a comparative overview of the studied conversations in terms of emoticons and emotes, i.e. Twitch-specific emoticons.

Figure 1:
General Iconographic Patterns in HasanAbi, The Young Turks, The David Pakman Show and Steven Crowder. Scraped during the Presidential Election Night 2020 live stream.

1. Introduction

Alternative political commentary is thriving on social media platforms such as Twitch and YouTube. The online culture wars — that were first ignited around 2014 (Nagle, 2017) — created a market of alternative micro-celebrities that sought to challenge, and eventually compete with, legacy media outlets. In her analysis of these “alternative influencers,” Lewis (2019) argued that their popular appeal stems from their canny performance of authenticity, which affords audiences a more intimate parasocial relationship with them. While there exists a growing body of literature on such new media influencer techniques (e.g., Baym, 2018; Abidin, 2018), much remains unknown about the participation of the audiences in this process.

Departing from this observation, this Digital Methods Winter School project seeks to examine how YouTube and Twitch afford audiences relatively new types of interactions with one another and with the influencers around whom these real-time communities form online. Empirically, this project presents three case studies of four alternative media creators performing live commentary during the 2020 U.S. Presidential Election: The Young Turks (TYT) and The David Pakman Show on YouTube and HasanAbi on Twitch and Steven Crowder on BlazeTV. We chose TYT as they host the oldest alternative political channel on YouTube, with over 5 million subscriptions. While TYT represents a relatively “established” alternative media organization, The David Pakman Show has a growing following on YouTube with over a million subscribers. HasanAbi was chosen for his novel presence and popularity on Twitch, an emerging (and under-studied) platform in relation to political commentary. Having worked for TYT, HasanAbi left the organization in January 2020 to stream his political commentaries on Twitch — claiming that Twitch allowed him to develop a more intimate relationship with audiences. Finally, we picked LouderWithCrowder as one of the remaining radical influencers on YouTube who is suffering from the new regulations as his live streams are sometimes interrupted and he no longer enables the ‘Super Chat’ function for audiences to comment during his shows.

2. Initial Data Sets

Using custom python-scripts, we collected millions of comments during the live streams of various political commentators on YouTube and Twitch during Election Night of the 2020 U.S. Presidential Election. We limited the operationalization of this data to three case-studies centered on four influencers (Table 1):

 

Table 1: Datasets Influencers

There were some limitations in our data collection procedure. Parts of comments pertaining to HasanAbi ’s live streamings on Twitch were not available for this study. However, sufficient comments were available for computational analysis and interpretative close- readings. Furthermore, we had to make a specific ethical decision about our study of audiences on BlazeTV. Audience engagement on BlazeTV was placed behind a paywall. In order to gain access to the data for this study a paid subscription was necessary. This also meant accepting the Terms of Use of BlazeTV. These terms of service stated that comments should not be scraped. However, a recent review of such terms of service by Fiesler et al. (2020) concluded that “it is an unsettled question as to whether it is explicitly illegal (or even a criminal act) to violate TOS” (188) and they “emphasize the importance of researchers making individual ethical judgments based on the specific circumstances of their research rather than relying on a TOS checkbox.” (195). In the end, we decided not to formulate a textual analysis of Crowder comments by scraping. Instead, we only mapped the emoticons, which were comparatively little in relation to the other datasets. We then formulated our qualitative observations of the platform.

3. Research Questions

Our overarching research question for this project was:

How did audiences express themselves in the chats of alternative live streams during the 2020 U.S. presidential elections?

Limiting this question to three sub-projects/ case-studies on Election Night, the following sub-questions were developed:

SQ1: How did audience engagement with HasanAbi on Twitch Live Stream during Election Night shape their sense of community?
SQ2: How did audience engagement with The Young Turks compare with The David Pakman Show during the 2020 US Election YouTube live streams?
SQ3: How did audiences of Steven Crowder engage on the alternative BlazeTV?

4. Methodology

This project has opted for a “netnographic” approach to gain insights into the audiences of alternative political commentators. Founder Robert Kozinets defined the approach in 2015 as “positioned somewhere between the vast searchlights of big data analysis and the close readings of discourse analysis” (2015, 22). Kozinets (2019) specified it as “a form of qualitative research that seeks to understand the cultural experiences that encompass and are reflected within the traces, practices, networks, and systems of social media” (26). While we depart from theoretical conceptions of “authenticity” and “intimacy”, this project aims for a more grounded theory approach. Such a more grounded approach aims at a creative and inclusive mapping practice as set out by the (revised) grounded theorists Strauss and Corbin (1998):

The important point for the researcher to remember is that the literature can hinder creativity if it is allowed to stand in between the researcher and the data. But if it is used as an analytical tool, then it can foster conceptualizations (Strauss & Corbin, 1998, 53).

Our methodology was then designed to first let general patterns emerge from the data and then perform qualitative close readings to “understand” those patterns in order to foster new thinking about political engagement on YouTube and Twitch.

Along with the three case studies of the main project, three sub-projects were created departing from the general method to use computational tools to identify specific patterns and then try to understand why these patterns were there. However, during the week, as we observed the visual aesthetics of the chats, we developed a parallel (overarching) project that mapped the general patterns in emoticon (YouTube and Blaze) and emote (Twitch) usage. The following sections will then first set-out the overarching project of mapping the iconography of the chats, while thereafter detail the specific approach taken per case-study.

Figure 2 presents a visual representation of the protocol used to obtain a map of a purely iconographic type, through which it was possible to obtain insights related to the entire thematic structure of the narrative set up around the alternative commentaries.

Figure 2: Visual representation of the protocol used to obtain a map of a purely iconographic type

Figure 2 shows (1) the departure from the datasets of the four influencers that were uploaded to 4CAT. Thereafter, (2) these datasets were exported to independent datasets of the live chat comment sections. Then, mainly due to logistics and technical manageability of the sample, we used a Python Pandas Script, to obtain a statistically relevant sample of 1/10 of the complete dataset (Steven Crowder was the exception to this approach for ToS reasons).

Having prepared the datasets, we (3) imported the data into Excel to perform the first analysis; isolating every comment containing at least one image (emoticon) in its body. In this process, the images were transformed, within the resulting CSV, through their actual HTML source code, thus making the implementation of the second step of analysis immediate. For this process, the VLOOKUP function of Excel was used to isolate, from time to time, the HTML elements, identifying the content immediately following the formula “<img src">”. Consequently, on a new column, the URL code of each image in the CSV ordered according to the scrape timestamp. In a new Excel spreadsheet, we then composed the source code necessary to display the images. Thereafter, exactly as in any text editor for HTML, the URLs are accompanied by blockquote, “src”, and a class that allows you to better manage the individual images within the web environment. The text was then copied into an HTML page of the text editor, and completed with the necessary metadata. The CSS class contains the stylistic functions of the code, allowing you to manage the size of the emoji, their position, interaction, and more. The webpage is then displayed locally on a Chrome browser. The Chrome extension GoFullPage can then be used to take a screenshot of the entire web page.

The last step (4) was to create an output that would best reveal the expressive power of images, and still give some context to the visualization. We, therefore, opted for a poster format. In essence, emojis were developed to facilitate the easy communication of emotion and feelings in content correspondence.

4.1 HasanAbi 's Twitch Stream

The focus of our research on HasanAbi 's Twitch Stream was to analyze the levels of interaction with the audience, specifically analyzing the aspect of intimacy, to see if we could pinpoint specific relations between the comments and the content. To examine this relation we looked at how HasanAbi elicits audience engagement. We used an archived version (Daily Dose of HasanAbi , 2020) of the commentator’s 16-hour live stream on Twitch called 2020 US PRESIDENTIAL ELECTION - BEDLAM IS UPON US!!!!!!!!!!!!!!!!!, which was originally posted on Twitch on November 3, 2020. The original 16-hour Twitch video content is no longer available, but the full stream can be rewatched on Youtube via a fan of Hasan Piker that posts a daily update of his stream.

The methodology for this part of the research project was based on determining the peaks in audience engagement in the statistics of the Twitch stream. The website Twitch Tracker (accessed on 05/01/2021), gives a timeline of the influencer’s statistics, indicating peaks of new subscribers (followers who pay a set amount every month to the streamer), number of concurrent viewers, and new followers.

Peaks in the number of new subscribers, followers, and concurrent viewers and their timestamp are mapped in Table 2:

Table 2: Peaks in the number of new subscribers (magenta), followers, and concurrent viewers and their timestamp. 1) Highest follower gain during the whole show, 2) Highest number of concurrent viewers during the whole show, 3) Fall after the peak in all numbers, 4) Second highest followers, 5) Noticeable fall in viewers, 6) Rise in subscribers since 04:10, 7) Highest number of subscribers

The highest peaks were further examined through a close reading of the recorded Livestream and analyses of the dataset from the chat (in 4CAT). This way we can analyze the interaction between HasanAbi and his audience and distinguish different types of interaction. In alignment with the overarching iconographic mapping project, we finally examined the most commonly used emotes to get a better understanding of the bigger picture through their visualizations chronologically. We used the top three emotes and “word-collocations” of 4CAT.

4.2 Super Chatting with The Young Turks and The David Pakman Show on YouTube

This section focuses on The Young Turks and The David Pakman Show. Departing from the collected data, we first mapped the emoticon use in the different chats to compare the engagement between the two. Based on those findings, we delved deeper into what happened in the live chat of The Young Turks. Using the “top vectors” module of 4CAT we mapped the most frequently used words in the YouTube chat of The Young Turks. After filtering out images and links, “word collocation” analyses were used to map relations between the top vectors and additional topics.

In order to visualize this discourse the “merged post text” (all the comments transformed into one string of plain text) collected through 4CAT, have been processed with open source Jason Davies Word Tree Generator to create a “graphical version[s] of the traditional ‘keyword-in-context’ method” (Davies n.d.; Wattenberg & Viegás 2008).

4.3 Alternative Engagement on BlazeTV

For Blaze TV we refrained from large computational approaches but we did collect emoticons that audiences were used to establish a pattern and compare that with the other chats that we studied. In total, we collected 3190 emoticons from the chat. By isolating single emoticons and maintaining their chronological order of appearance — according to their unique timestamp and frequency — the pattern has been constructed. We then performed close readings of the comments to see what type of engagement was happening on the platform.

5. Findings

This section presents the findings per case-study: (1) HasanAbi, (2) The Young Turks and The David Pakman Show, (3) StevenCrowder and BlazeTV.

5.1 Case Study I: HasanAbi, the “Older Brother” and “Buddy”

Hasan Piker is one of the most influential and powerful alternative political commentators on the progressive left side of the North American political spectrum and is aiming “to rewrite the narrative he sees in the news about the left” (Lorenz, 2020). Having worked for The Young Turks, HasanAbi left the organization in January 2020 to stream his political commentaries on Twitch full time. He claims that Twitch has allowed him to develop a more intimate relationship with audiences and that this transition offers him a better way to connect to a younger, broader audience (Lorenz, 2020). It is in this atmosphere of convivial familiarity that he assumes the role of Abi, which in the Turkish language means “the older brother” (Tureng, 2021). In one episode of Chapo Trap House, he states that he aims to reorganize a proper leftist representation of leftist views that much of the news coverage fails to properly address. In addition, he adds that “the younger generation is prone to reactionary politics so they need to question their political idols” (Piker, 2019). The chief operating officer of Twitch, Sara Clemens also confirmed that he “reached Twitch’s core viewership as millennials and Generation Z “(Lorenz, 2020). In this case, the older brother of the audience reflects the intention of his name choice. The term Abi has another colloquial meaning among speakers of the Turkish language and also means ‘buddy’, which also appears as his username on Reddit (r/okbuddyhasan). This is a translation of a frequently used term in American English ‘buddy’, that has strong social, historical, and cultural associations.

It is against the polarized backdrop of US politics that a significant rise of politically oriented content on Twitch became apparent; especially in the run-up to the 2020 Presidential Election. According to Streamlab, audiences on Twitch watched 3.4 million hours of Election Day coverage, HasanAbi ’s stream made up seventy-five percent of the total watched (May, 2020).

HasanAbi’s sixteen hour-long Election Night Livestream (in the category Just Chatting) was followed by 226,974 viewers. His audience interaction centered mostly on explanations of his political ideology and commentary during the analyzed live stream, during which he answered questions raised in the live chat. The information he shared was passionate and supportive in nature as he provided historical information and context in order to help his subscribers and followers to understand relevant news events.

To stimulate these intense interactive experiences, Twitch encourages the application of external extensions on Twitch (by third-party developers). The platform provides installation and user guides to improve their use. HasanAbi uses multiple Twitch extensions, such as “FrankerFaceZ” and “BeterTTV,” that let any streamer add custom emotes, which are only accessible to paying subscribers or those who unlocked channel points — a member rewarding system (Oh et al., 2020). These custom emotes exist next to Twitch basic emotes, that can be used by all users active in the platform’s chatting interface. HasanAbi has his unique channel emotes (to Woof), these lists of emotes clearly correspond with our findings (Figure 3). On both the FrankerFaceZ and BeterTTV websites it is possible to explore which unique emotes are available on streamers channels, and display which subscribed Twitch members submitted their emote creations and distinctive naming, such as “widepeepoHappy”. These custom emotes attest to subcultural practices on Twitch, as they are not only polysemic but have dynamic meanings and are highly specific compared to other online communities (Oh, et al., 2020). Interestingly, FrankerFaceZ keeps an up to date usage count of these specific emoticons for the entire platform, on the infinite wall the complete emotes collection is on display.

Figure 3: Emotes Pattern, HasanAbi Twitch stream. Scraped during the Presidential Election Night 2020 live stream. Reveals the use of unique emotes and the recently banned pogO.
Visual: Andrea Pronzati

PepeMeltdown is the most used animated emote of this stream (1230 times) (Figure 4)
This emoticon is used to express the tension about the election and live upcoming results, mostly combined with the profanity “fuck” (411 times in total dataset). This expression revealed the generally nervous atmosphere during the election day. Simultaneously PepeMeltdown was used to express feelings of anxiety for hurricane Eta that was approaching the US on the election day — but this was not as common as its usage in direct reference to the election.

Figure 4:
PeppeMeltdown was uploaded by the creator Uhavebadpc in 2018 on BeterTTV, and is available on 22,662 Twitch channels.

PepeMeltdown was followed by PogO (1126 times) (Figure 5), The PogO emote is one of the oldest on Twitch and is widely used by audiences to display excitement — “something terribly amazing” — in Livestream chats. The emote is mostly used together with the word “azan” (1054 times) which is in vowel rhyme with Hasan. HasanAbi uses “azan” to refer to himself — Azan Picker for Hasan Piker — along with his audience. PogO in combination with “azan” was mainly used by his audiences to express their fandom to HasanAbi.

Figure 5: This emote depicts the face of Ryan “Gootecks” Gutierrez and is permanently banned from FrankerFaceR. All emotes with “Gootecks” face have been banned from Twitch, as “the person depicted in it published tweets “encouraging further violence” following a riot at the US Capitol (Castro 2021).

MonkaSTEER (839 times) (Figure 6) on the third place is used mostly together with “ridin” (for riding, 1.016 times) and secondly with “riden” (248 times) which is “ridin” with an “e” to rhyme with Biden. These were used for stating “riding with Biden” which was very often used in the comment section to express the support for Biden or referring to being literally “on the way” to vote for Biden.

Figure 6: MonkaSTEER was uploaded by i__unno on BeterTTV in 2020

The Twitch extension FrankerFaceZ helps Hassan manage the appearance of his chat, as the affordances of this extension allow for “fine-tuning the Twitch experience” as the developers state themselves. The chat features offered by this extension are for example the dark theme (that HasanAbi uses), custom keyword highlighting, malicious URL blocking, and tabbed chat rooms.

The interaction between Hasan and his audiences, in general, can be divided into two main types: general or direct and personal. When many messages in the chat revolve around the same theme HasanAbi reacts more generally. However, HasanAbi more often responds directly to a single message. He reads the message out loud and reacts to the content or follows the URL in the message. For instance, when messages stated that Biden seemed to be losing, HasanAbi comforted the audience. In general, HasanAbi ’s stream - as with Twitch in general - is visually overwhelming with an abundance of interaction indicators. It is, therefore, that audience members employ several strategies to attract his attention. Figure 7 indicates some key features of the chat and audience strategies that we will set out in more detail.

Figure 7: Screenshot of HasanAbi ’s stream

First, 1a and 1b display donations made by audience members. They appear with an animated gif mocking right-wing alternative influencers such as Alex Jones (Figure 7, 1a). This is part of a broader style of connecting audience participation with an (online) battle against popular figures who do not politically align with the progressive politics represented by HasanAbi. This is a very explicit strategy as another example shows how audiences are stimulated to subscribe to HasanAbi as he tells them to keep “... giving me Bezos money!” (Figure 8).

Figure 8: Screenshot of “Get back at Jeff Bezos by giving me his money” banner

This includes a cartoon image of Hasan’s dog wearing a variety of hats and glasses that rises slowly from the bottom left of the screen every time he gains a subscriber or receives a donation. The dog appears with a speech bubble with the amount or number of subscriptions or the phrase “used Bezos Money!”

Second, Figure 7 (2), shows the icon badges in front of the usernames explaining the status and loyalty to Hasan’s channel (see Figure 9).

Figure 9: Screenshot of the representation of loyal members, connected to the duration of their membership.

These badges thus show how committed a commenting user is to the channel and, arguably, how well the person is embedded within the community. The Icon of the dog is custom to HasanAbi ’s Channel. Every Twitch streamer can design their unique icons.

Third, Figure 7 (3) shows how “@HasanAbi” mentions appear in a highlighted background color. The various colored usernames are ‘custom’ and can be changed with color codes added to each message in the chat. Our finding showed that most of the messages HasanAbi interacts with are ‘shout-outs’ to @HasanAbi (Figure 10).

Figure 10: This word tree shows the relation between the use of @hasanabi to generate attention and the formulation of questions and sharing of URLs.

Figure 10 provides an overview of the comment structure of “@hasanabi”. Here we can see that there are generally two types of strategies. First, asking a question about the opinion of HasanAbi. Audiences are keen to learn about his opinion about the topics they care about. Second, audiences direct their attention towards videos, news articles, etc. by providing HasanAbi with a URL.

Finally, Figure 7 (4) captured a moment that HasanAbi responds to a user’s suggestion, following a URL. HasanAbi ’s approach to the chat here is distinct from political commentators such as David Pakman, who rewards audience members who directly approach him through questions, comments, and subscriptions by mentioning them during the show. HasanAbi never mentions the usernames of people that message him or that subscribe to him.

5.2 Case Study II: Liberal Waves

This case study departed by observing two channels: The Young Turks and The David Pakman Show. Generating over 250 million views a month, The Young Turks is the self-proclaimed most “unapologetically progressive online news outlet” in the world. It is a multi-channel network, which is active on YouTube, Facebook, Twitch, Twitter, and linear TV channels such as YouTube TV, Roku, Pluto TV, and Samsung TV Plus. However, with over 5 million subscriptions, YouTube remains their main platform. They broadcast a daily web series focusing on news and current events. Originally created as a radio show in 2002, TYT’s founders Cenk Uygur, Ben Mankiewicz, and Dave Koller started to host political commentary on YouTube in 2005. Currently, the shows are co-hosted by Ana Kasparian and John Iadarola. On Election Day, The Young Turks received over 3 million views for their 13-hour live coverage from their studio in Los Angeles, remote locations, and Biden campaign headquarters.

David Pakman, on the other hand, started his career with a little Massachusetts community radio talk program in 2005. While Pakman got his show syndicated on several public radio stations, in 2009 he started to reach larger audiences on YouTube (inspired by The Young Turks). With “The David Pakman Show” he opened up his progressive political commentary to new audiences and reached over 1.2M subscribers by the end of 2020. His style on YouTube reflects his radio broadcasting background in the format of a news talk show that daily comments on mostly North American societal and political events. During the 2020 US election, Pakman covered (live) all the Presidential debates and live-streamed during the election night, while checking in with guests such as the Majority Report. His show is well known for its interviews with many fringe and/or extremist personalities in an effort to expose or hold accountable their political views. This in addition to hundreds of interviews with professors, scientists, lawmakers. His YouTube channel exists both out of a variety of hours-long live-streams and pre-recorded interviews, the short clips often are edited fragments of his live-streams.

When we compared the engagement of audiences with these channels on YouTube we found that whereas Pakman has a very supportive chat with people supporting himself (Pakman), his ideologies and Joe Biden, The Young Turks’ was filled with trolls and Trump supporters looking to make fun of progressives. This difference is quite well captured in Figure 11.

Figure 11: Emoji distribution for David Pakman (left) and The Young Turks (right)

Figure 11 shows that the David Pakman chat has laughing and blue hearts. A close reading of these comments indeed revealed a playful and optimistic mood in the chat that was complimenting Pakman and looking forward to a Democratic win for Biden. In contrast, The Young Turks chat was filled with popcorn, thumbs down, and wave emoticons. These emoticons expressed the dominant sentiment at the beginning of the chat that the Democrats would lose and that the hosts of The Young Turks would have a ‘meltdown’. In the rest of this section, we will delve deeper into the engagement with The Young Turks.

“Trump” is the most mentioned word in the chat (10258 times). The 4CAT word collocation function revealed that the word ‘Trump’ is most often mentioned in combination with ‘Trump voter’ (974 times), “shy Trump” (974), and “adown Trump” (972 times). The adjective “shy” used in combination with “Trump” or “voter” describes a Trump supporter who is reluctant to share their opinions out of fear of being judged for being a Trump supporter. This term is often used by Trump supporters and skeptic Democrats. The ambivalence of the word collocations ‘Trump voter’ (a vocal exclamation of support for the President), “shy trump” (a possible mockery of Trump supporters or used to indicate one's support of the President), and “adown Trump” (disapproval of the President), indicates a divide in the live chat’; the stream hosts both supporters and opposition for Trump.

This claim is further emphasized by the second most mentioned word: ‘water wave’, by a count of 10048 times. The water wave is used to refer to a “liberal meltdown”, as discovered through a close reading of the dataset: “a blue wave is coming! liberal meltdown wave that is!”. This could form a reference to The Young Turks’ live stream of the 2016 presidential elections, wherein the crew had a ‘meltdown’ on camera about the election of President Trump (Dame Pesos, 2017). However, the water wave emoji is also used in combination with the word ‘Biden’ or the blue heart emoji, indicating leftist support in favor of Biden for the presidential elections. Most notably about the use of the water wave emoji is its usage by bots that repeatedly spam the emoticon in the live chat (Figure 12).

Figure 12: Emoticon Patterns, The Young Turks YouTube live stream chat. Scraped during the Presidential Election Night 2020 live stream. Reveals ‘hating’ in the chat, and the use of the water wave emoticon representing The Young Turks (in 2016).

The third most used word mentioned in the chat is “maga” (4704 times), the acronym for Trump’s election slogan “Make America Great Again”. 4CAT word collocations reveals that “maga” is most often mentioned as “maga trump” (15 times), followed by “maga meltdown” (10), “trump maga” (10), “bye maga” (10), “meltdown maga” (8), “lol maga” (8) and “maga love” (8). This shows that both Trump supporters – trolls, in this case – as well as anti-Trump persons, are using the word “maga”. This suggests that (fervent) TYT viewers are “hating on” the pro-Trump supporters/trolls, also as a counter-response to the “hating” of the TYT stream.

Noteworthy are the comments about the physical appearances of two of The Young Turks’ hosts: Cenk Uygur and Ana Kasparian. The word ‘chunk’ is the ninth most frequently mentioned word (2512 times). ‘Chunk’ is used as an alternative for ‘Cenk’. This finding indicates that trolls are fat-shaming Cenk; shown in the word tree in Figure 13. It has become apparent that ‘Chunk’ is used in combination with the words ‘yogurt’, ‘cry’ and ‘ogre’.

Figure 13: Word Tree ‘Chunk’ displays the connection between the use of the word chunk to ogre and yogurt.

When audiences mention Ana in the live chat it mostly relates to her appearance (Figure 14).

Figure 14: Word Tree ‘Ana’ displays the commentary on her physical appearance

At the top of this word tree, it becomes obvious that audiences respond to and judge her ‘looks’, instead of her (in-depth) contributions during the stream. The majority of the expressions seem to be directed towards an aesthetic appreciation of Ana. Although, negative and humiliating comments appear which are pointing towards her nose-job and wardrobe choices.

5.3 Case Study III: “Radical” Alternatives

Steven Crowder is a highly popular Canadian-American right-conservative political commentator, active on YouTube and his own BlazeTV network. His show, Louder with Crowder is available through these channels and is also available in podcast form on Spotify and Apple Podcasts. Crowder is known for his comedy commentary style, which is also reflected in the regular Change My Mind segment. In June 2019, YouTube demonetized Crowder’s YouTube Channel after reports of harassment by Vox Host Carlos Maza. The platform re-monetized his channel after a year-long suspension in August 2020, which allowed Crowder to run ads next to most of the 2020 election content (published in fall 2020). In the run-up to the 2020 US Presidential Elections Crowder covered many streams, covering the Democratic primary debates, the (Vice) Presidential debates, and the Election itself (3 separate streams).

Leading up to the U.S. Presidential Elections 2020, the self-identified conservative comedy channel of Steven Crowder passed the threshold of 5 million subscribers. During the election show, Crowder received well-known guests including Donald Trump Junior, Senator Ted Cruz, Rudi Juliani, and Alex Jones. The seven and a half-hour-long Election Night live stream reached above 8 million views on YouTube alone. It is for this reason that the show was strongly competing with legacy media, such as Fox (14M) and CNN (9M) on cable news/television (Flood, 2020). This reflects Munger & Phillips (2020) argument that the “supply and demand” framework of YouTube is rapidly changing the field of political influence as it surpasses cable news viewership (4-5).

Besides the increasing viewer numbers on his publicly accessible YouTube channel, Crowder is active on multiple platforms and promises his audience unique content experiences behind the paywall of BlazeTV. Our expected finding was that BlazeTV allows Crowder to maintain an intimate relationship with his audiences while live streaming. Crowder’s highly tensible relation with YouTube, due to his harassing content and by repeatedly violating the platform policies, might have been the reason for this alternative channel on BlazeTV (Bergen, 2020). During the entire political run-up to Election Night Crowder’s live chat (and therefore his Super Chat) has been disabled. It was only on BlazeTv that his subscribed audience could interact during his stream through a live chat, without the threat for Crowder to be banned or de-platformed, due to misogynistic (audience) comment (Bond, 2018; Bergen, 2020).

Our analysis of BlazeTV, which was limited to qualitative observations due to ToS of BlazeTV, shows that there was only minimal subcultural engagement, or vernacular innovation present in the live chat of BlazeTV. Figure 15 shows the engagement in terms of emoticon use.

Figure 15: Emoticon Patterns, Steven Crowder BlazeTV, during the Presidential Election Night 2020 live stream. Support for a (conservative-oriented) US and Trump stood out, besides the expressions of joy due to the humorist performance of Crowder and guests.

By far the most used emoticon in the chat on BlazeTV was the American flag; a symbol that within the chat showed a sign of patriotism and loyalty to Trump and the U.S. While this symbolism reveals a lot about how patriotism has been connected with Trump, the other frequently used emoticons are rather “mainstream” and do not allow for much subcultural innovation. The emoji sentiment in this chat revealed mostly positive “smiley” expressions, according to emojipedia these “non-human yellow balls” tend to be used most to convey emotion (Broni 2020). The smiley’s, face-with-tears-of-joy and rolling-on-the-floor-laughing, are direct responses to the performance of Steven Crowder and his guest during the stream, expressing the entertainment levels of the audience.

Strikingly the use of emoticons also seemed to be a rare practice, evidently, the emotion pattern of Crowder is quite distinctive in relation to the visualizations of the other case-studies (Figure 16).

Figure 16: Emoticon Patterns, Steven Crowder BlazeTv during the Presidential Election Night 2020 live stream. It displays the minimal use of emoticons.

The emoticons appearing within the chat are among the most popular emoticons generally and universally used, according to the statistics of Unicode Consortium and emojipedia. While we could not perform large-scale quantitative analyses of hate-speech on the platform, our close readings revealed that there is very little radical engagement and that the texts match the relatively general mainstream Trumpist language used by the general public and in the more established right-wing press.

A final important discussion point that requires attention is that the audience responded heavily when YouTube went down during the stream of Crowder. This shows that many audiences engaged on BlazeTV were watching Crowders’ show on YouTube. The sentiment expressed, during the moment when Crowder’s channel was temporarily down on YouTube, ventilated the audience's fear that Crowder was being censored or (temporarily) banned from his main and most visible channel.

Debates and comments in the BlazeTV chat about payments, visibility, and loyalty, in relation to YouTube, raises the question of whether payment methods integrated into the affordances on YouTube (or Twitch) are preferred by audiences over alternative (behind the paywall) platforms. Unfortunately, LouderWithCrowder had his live chat disabled, and therefore no activated ‘Super Chat’ for us to investigate this idea further.

6. Discussion

This project looked at the way that audiences engaged with “alternative influencers” during the 2020 U.S. Presidential Election. Departing from a grounded theory approach we aimed to let patterns emerge in our exploration of three case-studies that we argue exemplify three prominent mediated experiences of contemporary politics. The following discussion sections will touch on three emerging themes from the analyses and relate them back to themes in the literature: (1) the relationship with the influencer, (2) the performance of intimacy through unified opposition, and finally (3) the problem of alternative paywalled platforms.

6.1 Performing Intimacy with the Influencer

Emotes and GIFs are crucial in the Twitch environment. Unlike emojis or emoticons, emotes and GIFs are completely user-generated and their codes are customized. Consistent with the platform’s name—Twitch—to express the state of vibing, like an involuntary nervous response, these emotes and GIFs have hyper loops, vibing very fast mostly horizontally, among a vertical fast-flowing flood of comments. HasanAbi ’s Twitch audience uses such emotes and GIFs in a very frequent and repetitive way. Because an emote or GIF takes more lines and screen space than a written chat message, audience members posting a chain of such visual comments can arguably be seen to gain visibility in the fast-moving and crowded chat stream. This can be seen to align with earlier studies on emojis in literary settings showing that such visual languages are equipped for upgrading the impact of the written message. However, on Twitch, it is not just the “universal” emoji language that creates the significance of a message or series of messages, it is about the strategic use of emotes to gain visibility within the community.

These emotes and GIFs are usually circulating on forums like Reddit. Emotes can have different sizes and emote names. “Pepe” the frog, for instance, is one of the most common characters in the Twitch universe, but the expressions and actions of the same character (nervous, driving, sad) have different names and sizes. The HasanAbi Twitch chats contained “pepemeltdown” , “monkasteer”, “widepeeposad” for example, —all Pepe’s doing different things and having different appearances.

There was very little evidence of hate speech and ‘hating’ in the HasanAbi sphere. HasanAbi ’s presence on Twitch appears to have encouraged younger people to engage with alternative political commentary as a form of entertainment. The prolific use of emotes and the complicated, personal and polysemic nature of their associated meanings is perhaps an indicator of the level of netnographic engagement that this kind of entertainment requires, while for the digital generation being now entirely “normal”. Twitch is primarily a video game live streaming platform that is a subsidiary of Amazon, however, it is quickly evolving beyond gaming (Storstein Spilker & Hansen 2020). The relevance of the Twitch/Amazon Prime synergy should not be ignored, since it is possible to subscribe to a Twitch channel through Prime membership at no additional cost. The duration of subscription and other factors that are associated with loyalty is important in the building of a relationship with the influencer, and are signified by different icons that accompany the screen name, which can lead to higher levels of visibility, engagement, and interaction.

HasanAbi in particular, as a micro-celebrity, performs various kinds of “affective labour” (Raun, 2018) such as gaming and political commentary. Thereby connecting to multiple news channels’ live videos, shifting through other social media platforms for newsgathering. HasanAbi thus provides authenticity (Woodcock and Johnson, 2019) as a form of intimacy when he constructs himself perfectly on Twitch as both a gamer and political commentator. Starting from the preference of platform and his name, Twitch provides the perfect environment for his commentary, as he wanted to be more intimate with his audience. Along with the interaction with his audience, HasanAbi also refers to other streamers on different platforms during his live streams and also creates specific response streams addressed to them, such as Steven Crowder. HasanAbi makes near-constant visual reference to the extreme right commentators by incorporating response memes that feature Alex Jones and Ben Shapiro into his screen space. This also provides a sort of interactive agenda that acknowledges the existence of conflicting opinions, creating an environment for multiple voices. HasanAbi can be considered as one of the most influential micro-celebrity figures who form the alternative political environment in the initially gamer-based nature of Twitch.

6.2 Performing Intimacy Through Unified Opposition

In contrast to David Pakman's audiences on YouTube, the analysis of The Young Turk’s chat stream showed that it was filled with hating audiences. Such audiences, however, tend to rely on similar visual communication tactics as “non-hating-audiences'' such as the use of the water wave emoji to make fun of The Young Turks’ hosts (or progressives in general) while at the same time expressing their support for Donald Trump. This points to the ambivalent meaning of water wave as a subcultural artifact that is used by different groups to express their political identity. As it refers back to the 2016 Election (“TYT Meltdown''), the use of the water wave emoji by the “hating” group of audience members, for example, can be seen to represent such in-group subcultural behavior.

Whitney Phillips describes this “trolling” behavior as constitutive humor, which is weaving influxes of ‘new’ experiences and “fetishized jokes” into a feeling of a collective us — the in-group (2017, 99). The behavior in The Young Turks live chat reveals a tension between opposing in-groups. Those supportive of The Young Turks and their political ideology, and those ‘intruding’ as an external group building a community that recognizes each other in fetishized laughter, mocking The Young Turks, resulting in a sense of ‘hating’ as their collective identity. These in-jokes are focused on us who laugh and clearly aimed at those who do not. This notion is intensified by the fact that these fetishized in-jokes are expressed in a space where The Young Turks audiences gather(ed) for their specific interests and cultural exchange. Our findings clearly show that the ‘intrusive’ (in-)group laughs together, turning The Young Turks and indirectly their audiences, into the object of that laughter. Therefore it is possible to state that these tensions generate an ambivalent space which complicates the togetherness and sharing experience of The Young Turks fanbase; alienating them by turning them into an “out-group unable to laugh” (2017, 92).

Our study points out that the objects for fetishized laughter are fat-shaming Cenk and the constant judgment of Ana’s appearance. A connection between this trolling behavior and the objects of these in-jokes can be drawn to Steven Crowder's Cenk (and Ana) impressions. Crowder targeted The Young Turks with these impressions, accompanied by other well known alternative influencers such as Ben Shapiro and Alex Jones, by running these as advertisements prior to the shows of The Young Turks on YouTube. This conspicuous behavior is, according to Phillips, inherent to the affordances of online and digital spaces (2017). Our study potentially shows the problematic amplification and interaction between alternative influencers, such as Crowder and his audience resulting in the “hating” behavior and loaded laughter in The Young Turks live chat. In this study, we did not (quantitatively) research audience migration between the opposing YouTube channels — The Young Turks and Steven Crowder. However, it would be relevant to investigate audience migration and channel crossing to gain more insights into the potential of mobilizing audiences to generate a communal identity and express their informed in-group (fetishized) jokes and vernacular.

6.3 The Problem of Alternatives

Audience participation is an important part of alternative political commentary. Be it in dialogue with the alternative political commentator, as represented by HasanAbi, or as a collective ‘hating’, as found on The Young Turks. The fact that Crowder had his Livestream temporarily suspended during the election and didn’t have a live chat function on YouTube affected the participatory experience of the audience. Although the increasing viewer numbers on his YouTube channel, Crowder is active on multiple platforms and offers his audiences unique content experiences behind paywalls. Crowder’s return to the conservative-media entity BlazeTV in January 2019 seems to be inspired by the demonetization of his YouTube channel, due to harassing content and violating the policies of the platform (Bergen, 2020).

It is potentially due to Crowder’s highly tensible relation with YouTube that the live chat, previously pairing his live streams, have been turned off to avoid misogynistic comments. Thereby forcing his audience to turn to BlazeTV for interaction. Our findings reveal that behind the paywall not much subcultural activity was taking place. This went against our expectations, as BlazeTV promotes itself as the largest free-speech and pro-conservative America news network, where Crowder’s audiences can engage with uncensored, not biased fact-checked, and limitless content (BlazeTV, 2020). One would expect that when not restricted by YouTube ’s guidelines, discussions can touch on multiple “controversial” topics.

This counterintuitive finding, however, resonates with Richard Rogers' argument that being de-platformed from an established platform as YouTube has extensive consequences for maintaining and increasing a “fan base, following and revenue” (2020, 226). As we revealed that subcultural activity was thinned and the expected ‘strong language’ turned out to be mild. Of course, we cannot make claims about to what extent radical audiences in Crowder's YouTube comments sections and live chats are the same as those on BlazeTV. Audiences mainly looking for radical engagement might, and most likely did, move on to other places than BlazeTV. From our study, however, it doesn’t seem that a paywalled platform is a good functioning alternative for audiences limited in their interaction on mainstream platforms.

Finally, it has become clear that Crowder, as well as YouTube, has financial motivations to collaborate. Crowder does not want to give up his primary distribution channel, and YouTube understands the value of the popular channel and its enormous audience engagement. It is therefore that Crowder explains that “[he] will play [by] the rules in their sandbox but they need to be consistent with them” (Bergen, 2020).

7. Conclusions

Against the context of a hyper-polarized US political landscape, this project explored how audiences are turning to openly ideological alternative political commentators, whose accounts they perceive to be more “authentic” than those of the “mainstream media”. As alternative political commentators continuously shape and formulate their political ideologies in hours-long live streams, audiences actively create — and maintain — intimate relations by performing subcultural practices — especially by proliferating visual cues.

While we were able to locate and map the dominant (visual) subcultural markers that serve as online mediators in the construction of intimacy, we did not thoroughly investigate how these markers relate to broader modes of interaction on YouTube and Twitch which are intricately linked with “gamified” payment systems. Features such as color-coded comments, customized emotes and emoticons, and distinctive membership badges can be seen to afford individual audience members more visibility, including increasing their visibility to the alternative political commentators. We, therefore, suggest that future research should explore how monetization and gamification afford relatively new modes of audience interaction.

8. References

Abidin, Crystal. 2018. Internet Celebrity: Understanding Fame Online. First edition. SocietyNow. United Kingdom ; North America: Emerald Publishing.

Baym, Nancy K. 2018. Playing to the Crowd: Musicians, Audiences, and the Intimate Work of Connection. Postmillennial Pop. New York: New York University Press.

Bloomberg.Com. 2020. ‘A Conservative YouTuber Thrives By Pushing Conflict With Site’, 12 October 2020. https://www.bloomberg.com/news/articles/2020-10-12/youtube-can-t-win-with-steven-crowder.

BlazeTV. n.d.. January 31, 2021. https://www.blazetv.com/page/aboutus.

Bond, Paul. 2018. “Glenn Beck, Mark Levin Create Conservative Media Powerhouse: Exclusive.” The Hollywood Reporter. December 2, 2018. https://www.hollywoodreporter.com/news/glenn-beck-mark-levin-create-conservative-media-powerhouse-1165665.

Broni, Keith. 2020. “Emoji Use in the New Normal.” Emojipedia (blog). May 1, 2020. https://blog.emojipedia.org/emoji-use-in-the-new-normal/.

Daily Dose of HasanAbi. 2020, November 5. HasanAbi ’s FULL ELECTION COVERAGE - HD IS NOT READY YET MY BAD - (Timestamps in Bio). [Video file]. YouTube. https://www.youtube.com/watch?v=CdR32JVBVDg&ab_channel=DailyDoseofHasanAbi.

Dame Pesos. 2016, November 13). The Young Turks Election Meltdown 2016: From smug to utterly devastated. [Video file]. YouTube. https://www.youtube.com/watch?v=ExrjcktO3PQ

Fiesler, Casey, Nathan Beard, and Brian C. Keegan. 2020. "No robots, spiders, or scrapers: Legal and ethical regulation of data collection methods in social media terms of service." Proceedings of the International AAAI Conference on Web and Social Media. Vol. 14.

Flood, Brian. 2020. “Fox News Election Night 2020 Coverage Draws 14 Million Viewers, Breaking All-Time Record.” Text.Article. Fox News. Fox News. November 4, 2020. https://www.foxnews.com/media/fox-news-election-night-ratings-all-time-record-update.

Kozinets, Robert V. 2015. Netnography: Redefined. 2nd edition. Los Angeles: Sage.

Kozinets, Robert V. 2019. Netnography: The Essential Guide to Qualitative Social Media Research. 3rd edition. Thousand Oaks, CA: SAGE Publications.

Lewis, Becca. 2018. “Alternative Influence: Broadcasting the Reactionary Right on YouTube.” Data & Society: Research Institute. https://datasociety.net/library/alternative-influence/.

Lorenz, Taylor. 2020. ‘How Hasan Piker Took Over Twitch’. The New York Times, 10 November 2020, sec. Style. https://www.nytimes.com/2020/11/10/style/hasan-piker-twitch.html.

May, Ethan. 2020. ‘Streamlabs and Stream Hatchet Live Stream Election Report’. Medium. 13 November 2020. https://blog.streamlabs.com/streamlabs-and-stream-hatchet-live-stream-election-report-cc9c7dd67136.

Munger, Kevin, and Joseph Phillips. 2020. ‘Right-Wing YouTube: A Supply and Demand Perspective’. The International Journal of Press/Politics. https://doi.org/10.1177/1940161220964767.

Oh, Soyoung, Jina Kim, Honggeun Ji, Eunil Park, Jinyoung Han, Minsam Ko, and Munyoung Lee. 2020. ‘Cross-Cultural Comparison of Interactive Streaming Services: Evidence from Twitch’. Telematics and Informatics 55 (December). https://doi.org/10.1016/j.tele.2020.101434.

Phillips, Whitney, and Ryan M Milner. 2017. “Constitutive Humor.” In The Ambivalent Internet : Mischief, Oddity, and Antagonism Online, 92-126. Cambridge, UK ; Malden, MA: Polity Press.

Piker, H. 2019, May 19. 316 - PBS: Permanent Revolution feat. Hasan Piker. [Audio podcast]. https://soundcloud.com/chapo-trap-house/316-pbs-permanent-revolution-feat-hasan-piker-51919

Raun, T. 2018. Capitalizing intimacy: New subcultural forms of microcelebrity strategies and affective labour on YouTube. Convergence, 24(1), 99–113. doi:10.1177/1354856517736983

Rogers, Richard. 2020. “Deplatforming: Following Extreme Internet Celebrities to Telegram and Alternative Social Media.” European Journal of Communication 35 (3): 213–29. https://doi.org/10.1177/0267323120922066.

Spilker, Hendrik Storstein, Kristine Ask, and Martin Hansen. 2020. “The New Practices and Infrastructures of Participation: How the Popularity of Twitch.Tv Challenges Old and New Ideas about Television Viewing.” Information, Communication & Society 23 (4): 605–20. https://doi.org/10.1080/1369118X.2018.1529193.

Strauss, A. L., & Corbin, J. M. (1998). Basics of qualitative research: Techniques and procedures for developing grounded theory (2nd edition). SAGE Publications.

Tureng. ‘Tureng - Abi - Türkçe İngilizce Sözlük’. n.d. Accessed 1 February 2021. https://tureng.com/tr/turkce-ingilizce/abi.

Wattenberg, M., and F.B. Viegas. 2008. ‘The Word Tree, an Interactive Visual Concordance’. IEEE Transactions on Visualization and Computer Graphics 14 (6): 1221–28. https://doi.org/10.1109/TVCG.2008.172.

Woodcock, Jamie, and Mark R Johnson. 2019. ‘Live Streamers on Twitch.Tv as Social Media Influencers: Chances and Challenges for Strategic Communication’. International Journal of Strategic Communication 13 (4): 321–35. https://doi.org/10.1080/1553118X.2019.1630412.