for SPIR Commenting cultures.docx.pdf Selected Papers of #AoIR2020:  The 21 ​st ​ Annual Conference of the  Association of Internet Researchers Dublin, Ireland / 28-31 October 2020 ‘PLEASE READ THE COMMENTS’: COMMENTING CULTURES ACROSS PLATFORMS Crystal Abidin Curtin University Platform-specific commenting cultures An old adage about the internet goes “Don’t Read The Comments”. It is a cynical word of caution from supposedly more experienced and savvy internet users, against a slew of negative, abusive, and unhelpful comments that are usually rampant online, stemming from trolling behaviour (Phillips 2015). “Don’t Read The Comments” has become an internet meme. Alongside parody websites (i.e. @AvoidComments n.d.), trawling through the comments section in search of ludicrosity has become an internet genre in and of itself. This comprises the likes of meme factory ‘The Straits Times Comment Section’ which collates absurd comments from users on a specific newspaper’s Facebook page (STcomments n.d.), as well as internet celebrity troll commentators like ‘American Ken’ M (Know Your Meme n.d.) and Singaporean ‘Peter Tan’ (Yeoh 2018), who post comments on a network of social media and fora in stealthily satirical ways that have even been co-opted for advertorials (Vox 2016). Such vernacular practice has in turn provoked a counter-genre of memes known as “I’m just Here For The Comments” (Tenor n.d.), in which users closely follow social media posts mainly for the resulting discussion and engagement in the comments section rather than the actual post itself. It is on this point of departure that this panel turns its focus to commenting cultures across platforms. Recent studies call attention to comment sections as hotbeds of trolling (Eberwein 2019), hostility (Murthy & Sharma 2019), and ‘dark participation’ (Quandt 2018). Negativity and toxicity has prompted calls for further inquiry on “how to counter incivility in comment sections,” (Ziegele et al. 2019: 17). Other studies have also explored the utility of comment sections, where users post comments to raise awareness for neglected topics or mistakes in news coverage (Heikkila et al. 2012), use flarf to Suggested Citation (APA): Abidin, C. (2020, October 28-31). ​‘Please read the comments’: Commenting cultures across platforms​. Panel presented at AoIR 2020: The 21 ​st​ Annual Conference of the Association of Internet Researchers. Dublin, Ireland: AoIR. Retrieved from http://spir.aoir.org. Virtual Event / 27-31 October 2020 Virtual Event regulate hate speech on Facebook (Abraham 2014), to pursue the truth (Eberwein 2019), and to vent frustrations (Pfeffer, Zorbach, & Carley 2014). Posting comments can also be useful for information seeking in online creative communities (Monroy et al. 2011). Proper attribution, or giving credit, has been found to be highly important in non-commercial creative communities (Meese 2014, Perkel 2016). However, unlike these case study approaches that have used specific incidents to highlight emergent user practices, this panel aligns more closely to a platform-approach – such as the study of Amazon comments and reviews as a mode of quantification and conversation-making (Reagle 2015) – and aims to cultivate macro perspective on platform-specific commenting cultures and ecologies. A conceptual matrix on platformed commenting cultures Across our papers, this panel aims to offer a conceptual matrix for studying platformed commenting cultures, comprising of: ● Structural affordances ● Algorithmic cultures ● Cultural, subcultural, and community practices ● Optimizing, circumvention, and gaming strategies ● Off-label uses The research questions we aim to address include: ● How central are comments and commenting cultures on each of these platforms? ● How do platforms prioritize comments through infrastructure and governance, and what is the impact of this on the normative culture of users? ● What are the platform circumvention and social circumvention strategies enacted by users, and how are these practices contentious or subversive? ● What methodologies and frameworks can be employed to study commenting cultures? ● What is the value of interrogating commenting cultures? The papers In this panel, we present a series of five papers that focus on a range of platforms and varieties of comment-centricity: The first paper looks at the pseudonymous nature of users on ​Reddit​, whose history of comments formulates their platform profile. The paper focuses on controversial moments in which Redditors are challenged on their identity and the norm of throwaway accounts. The second paper looks at ​Facebook ​ groups and communities that are centered on specific topics, whose appreciative and critical comments can evolve into earnest, playful, or spiteful flaming. The paper focuses on Facebook’s awarding of ‘Top Fan’ status that has led to practices of gamification and baiting. The third paper looks at ​9GAG​ meme genres that encourage its masculine-normative user base to comment actively. The paper focuses on how insiders/outsiders are demarcated through encoding/decoding wars, and how users construct stop gaps/safe spaces for baring vulnerability. The fourth paper looks at ​TikTok ​’s automatic attribution system that points to original sources of audio content and origin creators. The paper focuses on how users use comments to assert authorship and engage in information-seeking behaviour to wrestle ownership among each other. The last paper looks at ​Instagram ​’s changing commenting affordances as emblematic of shifts in social media platforms more broadly. The paper focuses on three of Instagram’s core tools to understand how public commentary culture is becoming more eclectic and ephemeral. This series of papers is a pilot attempt at formulating an ecology of commenting cultures on social media more broadly. While the apps selected have been developed in and influenced by specific ideo-geographies (3 in the US, 1 in China, 1 in Hong Kong), and boast a range of posting types (2 text-based, 2 visual-based, 1 audio-based), future progress and extension of this research aims to focus on a more diverse range of apps especially in the Global South and in non-English languages. We hope to use our AoIR panel as a springboard for future collaborations. References Abraham, B. 2014. “Challenging Hate Speech with Facebook Flarf: The Role of User Practices in Regulating Hate Speech on Facebook.” ​The Fibreculture Journal​ 23. Eberwein, T. 2019. ‘“Trolls” or “warriors of faith”?: Differentiating dysfunctional forms of media criticism in online comments.’ ​Journal of Information, Communication and Ethics in Society​ (Online first) Heikkilä, H., Domingo, D., Pies, J., Glowacki, M., Kus, M., & Baisnée, O. 2012. Media Accountability Goes Online A transnational study on emerging practices and innovations, (14). Know Your Meme. n.d. ‘Ken M’. ​knowyourmeme.com. Meese, J. 2014. It Belongs to the Internet: Animal Images , Attribution Norms and the Politics of Amateur Media Production. ​M/C Journal ​, ​17 ​(2), 1–6. Monroy-Hernandez, A., Hill, B. M., Gonzalez-Rivero, J., & Boyd, D. 2011. Computers can’t give credit: How automatic attribution falls short in an online remixing community. Conference on Human Factors in Computing Systems - Proceedings​, 3421–3430. Murthy, D., & Sharma, S. 2019. Visualizing YouTube’s comment space: online hostility as a networked phenomena. ​New Media and Society​, ​21 ​(1), 191–213. Perkel, D. 2016. Share wars: Sharing, theft, and the everyday production of Web 2.0 on DeviantArt. ​First Monday​, ​21 ​(6), 1–24. Pfeffer, J., Zorbach, T., & Carley, K. M. 2014. Understanding online firestorms: Negative word-of-mouth dynamics in social media networks. ​Journal of Marketing Communications​ 20(1-2): 117-128. Phillips, W. 2016. ​This is Why We Can’t Have Nice Things: Mapping the Relationship Between Online Trolling and Mainstream Culture​, Cambridge; London: MIT Press. Quandt, T. (2018). Dark participation. ​Media and Communication​, ​6 ​(4), 36-48. Reagle, J.M. 2015. ​Reading the Comments: Likers, Haters and Manipulators at the Bottom of the Web ​, Cambridge; London: MIT Press. STcomments. n.d. ‘The Straits Times Comment Section.” ​Facebook.com. Tenor. n.d. ‘Im Just Here For The Comments GIFs.” ​tenor.com. Vox. 2016. ‘The world’s greatest internet troll explains his craft.’ ​YouTube.com, ​6 May. Yeoh, G. 2018. ‘Who is Peter Tan, the Mysterious #1 Commenter of ST’s Comments Section?’ ​ricemedia.co, ​21 March. Ziegele, M., Naab, T. K., & Jost, P. (2019). Lonely together? Identifying the determinants of collective corrective action against uncivil comments. ​New Media and Society​, 1-21. @AvoidComments. n.d. ‘Don’t Read The Comments.” ​Twitter.com. KARMA, THROWAWAYS, AND POST HISTORIES: COMMENTING CULTURES ON REDDIT Emily van der Nagel Monash University “Don’t read the comments”: Criticism and gendered harm In this paper, I examine a genre of posts that call others out for inconsistent comments to argue that cohesive identities remain important on the largely pseudonymous social media platform Reddit. Analysing posts that reference comment histories in the subreddit r/QuitYourBullshit evidences a need for people to post consistent identity information. Beginning with the common exhortation “don’t read the comments” means acknowledging that internet culture is often fraught. Titling a report ​Don’t Read the Comments: Enhancing Online Safety for Women Working in the Media​ (Gender Equity Victoria 2019) casts comments as a vehicle for sexist harassment and abuse that undermines women journalist’s professionalism. Journalist Jessica Valenti made a case for ending comment sections in online news, arguing that “comments uphold power structures instead of subverting them: sexism, racism and homophobia are the norm; threats and harassment are common” (Valenti 2015 n.p.). A browser extension that automatically hides comment sections boasts that it “puts an additional layer of decision between the habitual scroller and the waste of attention that awaits” (drestuart 2019 n.p.). An argument by communication scholar Joseph Reagle that comments are the “bottom half of the web” (2015: 1) investigates comments as a reactive genre of communication that has the potential to inform and entertain, but are also easily manipulated, and can be used to harass or troll. While this broader online commenting culture is considered an often troubling territory rife with gendered harassment and of little value to blogs and news, on Reddit, comments animate the entire platform. Reddit: A comment-led platform culture Comments on Reddit appear on posts within specific subreddits, which provide contexts for conversations. Comments can be upvoted, granting the user karma points and pushing the comment towards the top of the list, or downvoted, which risks the comment being hidden. Reddit co-founder Steve Huffman introduced comments to his platform of submitted links in 2005, finding the addition immediately validating: “All of a sudden, links to articles elsewhere online became their own dynamic pages, containing discussions between real people” (Huffman in Lagorio-Chafkin 2018: 76). Reddit threads comments together, which keeps all the responses to an initial comment together, structuring the comments section and allowing conversations to splinter off into smaller discussions as comment sections grow. A number of research papers investigate the cultures of specific subreddits, framing them as a community in the process. On r/Mexico, people give direct, encouraging advice in both Spanish and English (Glide 2018). Fans of the true crime podcast Serial discuss the latest episode on r/Serial, but also critique the US criminal justice system (Buozis 2019). A lesbian subreddit was found to explicitly accept and celebrate identity-based differences, rather than policing the boundaries of the lesbian identity (Foeken & Roberts 2019). Active members of subreddits often share common interests and goals. But this doesn’t mean that subreddits are simply harmonious communities that exist as peaceful islands. r/Quit Your Bullshit: Reddit cultures clashing Unlike social media platforms that have “real name” policies, such as Facebook, Redditors are largely pseudonymous. Instead of a list of personal information, a Reddit profile displays the most recent posts and comments someone has made. In this way, someone’s comments almost become their profile. This can lead to conversations, and even accusations, around identity. An entire genre of posts to subreddit r/QuitYourBullshit involves people challenging others on their Reddit identities. One post to r/QuitYourBullshit describes the contradiction in the title: OP [original poster] is saying that he was thrown in jail for six months for DNA [fraudulently claiming that an Amazon package Did Not Arrive] but if you check his post history you can see that he posted something about DNA just 99 days ago (GamingManiac989 2019 n.p.). In a screenshot posted by Fun11111 (2019), a Redditor’s post to a question and answer subreddit, “I’m 7’1 AMA [Ask Me Anything]” was countered by another user: Based on your post history you are an interesting guy. Make $2m per year, grew from 6’6” to 7’11” in less than 3 weeks, you are a Harvard admissions officer while only just sitting your SAT, while struggling to get a drivers license despite owning several luxury cars. Or you are just making shit up. Checking someone’s post history for comments that contradict them or reveal some other foolishness are common enough that on meta-subreddits like r/UnpopularOpinion or r/TheoryofReddit this is discussed as a tactic. “Looking through someone’s post history to “win” an argument is stupid”, says DarthKittie (2019). The distinction between r/QuitYourBullshit posters seeing post history as legitimate material for challenging someone on their identity, and other subreddits disparaging this as a petty tactic, shows that Reddit is not a monolithic culture, but is comprised of subreddits and Redditors that may hold opposing views, but often interact. When comments become essential identity information, the need for this identity to be presented coherently and consistently demonstrates that Redditors are invested in a kind of pseudonymous authenticity as a foundation for their communities to be built on. References Buozis, M. 2019. ‘Doxing or Deliberative Democracy? Evidence and Digital Affordances in the Serial Subreddit’, ​Convergence​, vol. 25, no. 3, pp. 357–373. DarthKittie. 2019. ‘Looking Through Someone’s Post History’, r/UnpopularOpinion, Reddit​, viewed 21 February 2020, https://www.reddit.com/r/unpopularopinion/comments/dypnwa/looking_through_someon es_post_history_to_win_an/​. drestuart. 2019. ‘Don’t Read The Comments!’, ​Chrome Web Store​, 2 January, https://chrome.google.com/webstore/detail/dont-read-the-comments/nlhmhpppjnlbdfgebi nkgjiljipnejbe?hl=en​. Foeken, E & Roberts, S. 2019. ‘Reifying Difference: Examining the Negotiation of Internal Diversity on a (Post-)Lesbian Subreddit’, ​Sexualities​, vol. 22, no. 7–8, pp. 1268–1287. Fun11111. 2019. ‘Bruh the Patience’, r/QuitYourBullshit, ​Reddit​, viewed 21 February 2020, https://www.reddit.com/r/quityourbullshit/comments/dhmmd3/bruh_the_patience_you_h ave_to_have_just_to_check/​. GamingManiac989. 2019. ‘OP Is Saying’, r/QuitYourBullshit, ​Reddit​, viewed 21 February 2020, https://www.reddit.com/r/quityourbullshit/comments/cxnkoh/op_is_saying_that_he_was_ thrown_in_jail_for_six/​. Gender Equity Victoria. 2019. ‘Don’t Read the Comments: Enhancing Online Safety for Women Working in the Media’, ​Media Entertainment and Arts Alliance​, 18 December, viewed 21 February 2020, https://www.meaa.org/download/dont-read-the-comments-enhancing-online-safety-for-w omen-working-in-the-media/​. Glide, M. 2018. ‘¿Cuáles son sus recomendaciones?: A Comparative Analysis of Discourse Practices Implemented in the Giving and Seeking of Advice on a Mexican Subreddit in Both Spanish and English’, ​Current Issues in Pragmatic Variation​, vol. 15, no. 1, pp. 181–207. Lagorio-Chafkin, C. 2018. ​We Are the Nerds: The Birth and Tumultuous Life of Reddit, the Internet’s Culture Laboratory​, Piatkus, London. Reagle, JM. 2015. ​Reading the Comments: Likers, Haters, and Manipulators at the Bottom of the Web ​, MIT Press, Cambridge. Valenti, J. 2015. ‘Not All Comments Are Created Equal: The Case for Ending Online Comments’, ​The Guardian​, 10 September, viewed 21 February 20202, https://www.theguardian.com/commentisfree/2015/sep/10/end-online-comments​. TROLLS, HATERS AND CONSPIRACY THEORISTS: FACEBOOK COMMENTING CULTURES DURING THE AUSTRALIAN SUMMER OF BUSHFIRE Amelia Johns University of Technology Sydney Francesco Bailo University of Technology Sydney Introduction Scholars have long examined how platform affordances enable user expression, social interaction, and public deliberation around key issues (Hille & Bakker 2014, Kavada 2012) while they manipulate and constrain those expressions, orienting users toward desired forms of engagement (boyd 2010, Gillespie 2019, Ben-David & Soren 2019). From this perspective posts that generate large numbers of reactions, comments and shares are recommended by platform algorithms, regardless of the quality of the content. Scholars have examined how these platform aspects have allowed misinformation and hate speech to be spread (Gillespie 2018, Wooley & Howard 2019). But often what happens ‘below the line’ in the comments section is overlooked, or attention goes to large coordination efforts, for example examining the Russian troll farms that use bots and sock puppet accounts to manipulate conversations for the purposes of propaganda or profit in the US elections of 2016 and beyond (Wooley & Howard 2019). This overshadows a focus on more mundane, everyday commenting cultures and subcultures, where commenters may engage earnestly with posts to share their world-view and contest others, or use provocative tactics to hack the narrative and misdirect the reader, for example by shitposting (Phillips & Milner 2017) or manipulating and subverting algorithms by spamming users for purposes of activism or just mischief (Phillips 2015, Phillips & Milner 2017). More problematically these ‘ambivalent’ cultures also extend to trolling, flaming and doxing (Phillips 2015, Reagle 2015) or spreading conspiracy theory, falsified information and hateful memes (Wooley & Howard 2019, Gillespie 2018) weaponising the comments sections of news organisations and public social media sites. ​Facebook’s ‘toxic’ commenting cultures in the Australian summer of bushfire Facebook is a platform that has become closely associated with these toxic commenting cultures. In spite of their real-name policy which some claim limits the incivility commonly associated with anonymous comment (Reagle 2015: 9, Ben-David & Soren 2019), the platform has been associated with #Pizzagate and #QAnon conspiracy theories among others, with comments amplifying and boosting problem content. Facebook’s recommendation algorithm has also been argued to connect far right, conspiracy theory and hate groups into networks of hate and disruption. This was demonstrated during Australia’s summer of bushfires, with reports identifying Facebook posts sharing conspiracy theory and climate change denialism posted in right-wing and nationalist pages and amplified out from there (Ryan & Wilson 2020). Nonetheless reports have tended to regard the outcome of problematic commenting cultures and subcultural practices as always counter-productive to democracy, and those who share or respond to the comments are regarded as cultural dopes rather than active and literate audience members. To provide a more balanced account this paper uses a mix of computational and ethnographic methods to examine the comments sections of 6 Facebook pages, 2 from online and legacy news organisations, 2 from Australian nationalist and far-right pages, and 2 from the official pages of conservative politicians which were during Australia’s recent summer of bushfire. The questions leading the analysis are: Q1 What users/communities are found in the online conversation, and how are they connected? Q2 Who are the so-called ‘super-spreaders’ and what are their motivations for posting comments deemed to denigrate or misinform? Q3 What folkloric elements and vernacular expressions were observed in the comments sections of popular news articles and Facebook pages focused on the cause of the fires, and do commenting cultures differ according to generational difference? Methodology The paper presents initial findings from a larger project which maps the diffusion of social media discussions focused on 4 contentious topics: climate change, vaccination hesitancy, immigration and LGBTIQ+ issues. Firstly, we used an innovative ethnographic mapping method using Wikibase ( ​https://wikiba.se/​). The ethnography began with sustained observation and field note recording of the comments sections of Australian legacy news postings (The Guardian, ABC, SBS, The Australian, Herald Sun, Sydney Morning Herald, Daily Telegraph and Age newspaper). The ethnographic mapping method was used to identify relevant opinions, pages, users and personas, and to connect them through a set of themes. Facebook’s recommendation algorithm was exploited to broaden out the list of pages observed, producing a non-representative sample of fringe conversations during the bushfire event. A large scale analysis of Facebook interactions was then conducted by searching Crowdtangle database. The search generated a list of 314,829 posts from 21,093 pages. Outgoing links from the Facebook pages involved in the conversation were used to cross-check against the wiki map and broaden sources, relate pages together and to identify communities around similar linked resources (e.g. videos, news articles, Facebook posts). Quantitative and qualitative approaches were then used to map the conversation on two different dimensions, a thematic dimension and a network dimension. These two dimensions help to answer Q1 and Q2 but also inform the sampling of the Facebook comments. Finally, we used a customised scraper to collect the comments section of the most relevant postings, parsing the body of the message, along with the username, creation time, number of reactions and relations to the other postings (i.e. “reply to”). This data was automatically coded for the presence of themes and opinions identified ​a posteriori​ based on a dictionary of key terms. A content and discourse analysis of individual comments and interactions between comments was then conducted to answer Q3. The results will be discussed in this paper. References Abidin, C. 2018. Internet Celebrity: Understanding Fame Online, Bingley, U.K: Emerald Publishing. boyd, d. 2010. Social network sites as networked publics: Affordences, dynamics, and implications. In V. Papachrissi (Ed.), N​etworked self: Identity, community, and culture on social network sites​ (pp. 39–58). New York, NY: Routledge Ben-David, A., & Soffer, O. 2019. User comments across platforms and journalistic genres. ​Information, Communication & Society​, 22(12), 1810–1829. Gillespie, T. 2019. ​Custodians of the Internet: Platforms, Content Moderation and the Hidden Decisions that Shape Social Media​. New Haven; London: Yale University Press. Hille, S., & Bakker, P. 2014. Engaging the social news user: Comments on news sites and Facebook. ​Journalism Practice​, 18(5), 563–572. Kavada, A. 2012. Engagement, bonding, and identity across multiple platforms: Avaaz on Facebook, YouTube, and MySpace. ​MedieKultur: Journal of Media and Communication Research​, 28(52), 28–48. Phillips, W. 2016. ​This is Why We Can’t Have Nice Things: Mapping the Relationship Between Online Trolling and Mainstream Culture​, Cambridge; London: MIT Press. Phillips, W. & Milner, R. 2017. ​The Ambivalent Internet: Mischief, Oddity and Antagonism Online​. Cambridge, MA: Polity. Reagle, J.M. 2015. ​Reading the Comments: Likers, Haters and Manipulators at the Bottom of the Web ​, Cambridge; London: MIT Press. Ryan, H. and Wilson, C. 2020. As Australia Burned, Climate Change Denialism Got A Boost On Facebook, ​BuzzFeed News​, 23 Jan 2020, Viewed August 14: https://www.buzzfeed.com/hannahryan/facebook-australia-bushfires-climate-change-de niers-facebook Wooley, S.C. & Howard, P.N. 2019. ​Computational Propaganda: Political Parties, Politicians and Political Manipulation on Social Media​; NY: Oxford University Press. ‘FEELS BAR’ AND MASCULINE VULNERABILITY: COMMENTING CULTURES ON 9GAG Crystal Abidin Curtin University 9GAG 9GAG is a pseudonymous social media app with integrated social media platforms and a website where users can upload and share original or external content usually focused on meme cultures. Headquartered in Hong Kong and boasting several prolific tech industry investors, it was founded in 2008 and boasts over 150 million international users on its Facebook, Twitter, and Instagram accounts alone. Users post image and video memes that can be upvoted, downvoted, and commented on. User responses and the algorithmic blackbox decide whether posts are filed under the ‘Hot’, ‘Trending’, or ‘Fresh’ tabs. Comments too can be upvoted, downvoted, and replied to. Clicking on a 9Gagger’s handle reveals their homepage/feed of posts (contingent upon subscriptions and platform footprints), posts they have contributed, and posts on which they have commented or replied. However, the design of 9GAG (on desktop and mobile app) focuses on individual posts rather than individual users/handles as the main site of reputation building. As such, post-specific comment subcultures and subcommunities proliferate. Among the diverse genres of meme cultures, early users of 9GAG would occasionally share confessions, seek advice, or pour out laments specifically pertaining to romantic relationships (Figures 1 & 2). This was against the backdrop of early 9GAG culture being hyper-masculine (Veronica & Handoyo 2016), populated by men who struggle with relationships with women (Anggiarima 2013) and who are ‘forever alone’ (Kusuma 2018), and having gendered communication norms that required brokerage (Dewi 2017, Saputri 2018). Figures 1 & 2: 9GAG memes about romantic failure. Eventually, when 9GAG streamlined its posts into over 24 different sections in early 2017, the subcategory of “Relationships” became institutionalised as a bona fide content stream. This legacy of relationship chatter on 9GAG has evolved into a period comment-focus genre of meme posts known as the ‘Feels bar’. These come in the form of a specific image meme posted to 9GAG and a title declaring that ‘the feels bar is open’ (Figures 3 & 4), in which the original poster (OP) invites other (male) users to make agony-aunt like confessions and disclosures in the comments section. In response, OP and other users provide advice and care, and at times reciprocate with confessions of their own to foster a culture of sharing in a safe space. Figures 3 & 4: The template ‘feels bar’ meme soliciting interactions in the comments section. Methodology This paper interrogates the normative commenting cultures on 9GAG at large, by way of juxtaposing this to the stop gap and safe space of the ‘feels bar’, which is utlilized by 9Gaggers as transient and occasional counseling sessions. The data is draw from a multi-year immersion and experience of 9GAG as a participant observer (2010–), and more concerted digital ethnography and content analysis of ‘Hot’ posts (June 2019–). Platform norms and ‘feels bar’ The key commenting norms on 9GAG include: ● Assumed pseudonymity ​, wherein users do not need to disclose personal information while mostly maintaining a consistent handle; at times, verification is volunteered in the form of a personal photograph revealing one’s face, often to instigate sincere reciprocity and relationship building in the comments (Figures 5-7) Figures 5-7: Post and two comments in response to the OP’s self-disclosure. ● Digital dualism ​, in that interactions on the platform are taken at face value without any overt identity linkage to ‘offline’ or ‘IRL’ selves; occasionally, members reveal images divulging a slice of their lives especially if they have high status in society (Figures 8 & 9) in a meme format known as ‘9Gaggers in the wild’ or ‘one of us’. Figures 8 & 9: Posts wherein OPs share a ‘slice of life’ or their status in society. ● Gated ‘feels bar’, ​wherein vulnerable disclosures, the soliciting of emotional support, and the provision of counseling and friendship has to be confined only within ‘feels bar’ invitations; content ‘bleeding’ by users who post ‘feels’ without first kicking off a post for others to participate/reciprocate tend to register lower engagement (Figure 10), although some users may post the meme in various comments sections as suggestion that another ‘feels bar’ post is due (Figure 11). Figures 10 &11: Post and comment about ‘feels bar’ outside of designated ‘feels bar’ posts. ● Expressions of gratitude, ​wherein users who have previously benefited from the homosocial support in ‘feels bars’ return to thank others in a new standalone post; such new posts serve as bookends of personal crises that have concluded, spread awareness of the ‘feels bar’ as an important node of congregation, and celebrates the 9GAG community at large (Figures 12 & 13). Figures 12 & 13: Posts expressing gratitude for support received on 9GAG through comments sections. ● Comment trains, ​wherein early commentators are usually responsible for setting the tone and shape of conversation under a post, be this participating in the digital ‘feels bar’ while being in actual bars (Figure 14), or shitposting ‘dank memes’ to cheer an OP up through sarcastic and self-deprecating humour (Figures 15 & 16). Figure 14: An example of a comment train. Figures 15-16: Another example of a comment train. Continued research The preliminary analyses (–Feb 2020) presented here will be extended as the study continues and considers the potential of ‘comment’ pods, issues of misogyny and feminism, and possible inter-cultural intersectionality present in the confessional disclosures, in light of the subsequent ‘Americanization’ of the site (Achadiat 2013) and observed racism (Kusuma et al. 2016) despite 9GAG originally surging in popularity among Southeast Asian users from the late-2000s to mid-2010s. As the app becomes more global with an international audience, language- and culturally-specific humour norms will reshape the meme-making and commenting cultures of this space. At the time of writing, it appears that commenting cultures are slowly wrestling away attention from main posts, as users express enthusiasm towards ‘camping out’ in the comments section (Figures 17 & 18). Figures 17 & 18: Memes depicting commenting culture overtaking posting culture. References Achadiat, R. A. 2013. ‘The representation of Americanization myths in the internet memes on the 9gag comedy website.’ ​Passage ​1(2). Anggiarima, P. 2013. ‘Gender Stereotypes in www.9gag.com: A Discourse Analysis.’ Thesis, English Department, Faculty of Letters, State University of Malang. Dewi, C. 2017. ‘Different language styles in male and female comments on meme in 9GAG.’ Sarjana Sastra Thesis, English Letters Study Programme, Faculty of Letters, Sanata Dharma University. Kusuma, H. 2018. ‘Illocutionary acts in ‘Forever Alone’ memes in 9GAG.com website.’ Sarjana thesis, Universitas Brawijaya. Kusuma, G. N. A., W. Suamajaya, and N. K. A. Suwastini. 2016. ‘The identification of racism in internet meme comic at 9gag.com.’ ​JURNAL Pendidikan Bahasa Inggris Undiksha ​4(2). Saputri, E. R. P. L. 2018. ‘Humor types and gender stereotypes found in 9GAG rage comics memes.’ Sarjana Pendidikan Thesis, English Language Education, Faculty of Teachers Training and Education, Sanata Dharma University. Veronica, V., and O. F. Handoyo. 2016. ‘Reading masculinity on 9GAG.’ ​Kata Kita, ​4(3). DOES ANYONE KNOW WHO MADE THIS?: COMMENTING CULTURES ON TIKTOK Aleesha Rodriguez Queensland University of Technology D. Bondy Valodinos Kaye Queensland University of Technology Patrik Wikström Queensland University of Technology Introduction TikTok, a short video platform owned by Chinese tech giant Bytedance, was a breakout digital media platform in 2019. The platform hosts algorithmically recommended short videos (15-60 seconds) and affords users a variety of tools to create, share, and interact with content. TikTok also boasts a unique comment section that sets it apart from other platforms discussed in this panel. This study explores how two aspects of TikTok’s platform infrastructures, comment filtering and automatic attribution, influence comment cultures on the platform. With millions of videos being added every hour, success for TikTok creators relies on capitalizing on the latest hashtags, trendy memes, and popular audio. Similar to its progenitor, lip-synching platform Musical.ly, audio can be recorded alongside video, imported from TikTok's internal library of songs and clips. Audio clips can also be taken directly from another TikTok user's video. In the cases of audio files taken from other users, the newly created video will display the previous creator as the original creator of the audio. TikTok’s ‘automatic attribution’ system (Monroy-Hernandez et al. 2011) has created issues for creators by misattributing audio to the wrong source. This, in turn, leads to a culture of information seeking (e.g. “Does anyone know the name of this song?”) and asserting authorship in the comments (e.g. “Hey! This is my song! Like this comment [for visibility]”). Comments on TikTok are moderated algorithmically that reflects prevailing conditions in Bytedance’s original market, China. Strict moderation of user generated content, including comments, is mandated in China (Cybersecurity Administration of China 2017) as part of a broader State program of shaping discourse (Keane & Su 2018). Previous research has found obscenity and profanity to be key targets of comment censorship (Song & Wu 2019) in addition to video content on short video platforms (Lin & de Kloet 2019). In addition to commenting to engage with video content, creators, or other users, posting comments can also be useful for information seeking in online creative communities (Monroy et al. 2011). Proper attribution, or giving credit, has been found to be highly important in non-commercial creative communities (Perkel 2016, Meese 2014). The right to attribution is a protected copyright in many jurisdictions (Hansmann & Santilli 1998), but copyright cultures in China are much different than in the global West (Montgomery 2010). China has built a much more robust copyright culture over the past two decades but communal practices and sharing culture have deep roots in Chinese society (Han 2018). This difference in approach to copying and attribution is evident in the fact that during the first six months of 2019, TikTok only reported removing 3345 videos due to copyright infringement (TikTok 2020), while YouTube reported removing over 16 million (Google 2019). In response, unique comment cultures have emerged in TikTok’s comment section. Methodology To study comment cultures and attribution on TikTok, we have developed a novel scraping tool to collect video, audio, and comment data from TikTok. Our scraping system uses a custom script to collect video, audio, comments, and metadata from TikTok. In March 2020, we collected a sample of 999 TikTok videos that included #fyp (for you page), a popular hashtag associated with more than 100 million posts. Following our scrape, we developed initial qualitative coding themes to investigate (mis)attribution practices on the platform and through this process isolated 71 videos (with a combined total of 90,776 comments) to further explore commenting cultures on TikTok. We then conducted a grounded descriptive analysis of the comments under each isolated video to query if t commenters engage in information seeking behaviour and assert authorship, as well as, study broader patterns of commenting culture on TikTok to answer questions such as, how does it appear that the platform filters comments? Initial Findings and Progress to Date Our initial findings suggest that users do indeed engage in information seeking behaviour for songs that are misattributed by TikTok’s automatic attribution system. Further, we have found evidence to support that TikTok commenters use the comment section to assert authorship. Our grounded qualitative analysis of videos revealed a handful of ways TikTok creators and users use the comment sections to overcome attributional issues. In one example, a TikTok creator and music producer showed up in the comments of a video that was using the creators’ audio but misattributed to another video and creator. The creator’s post claiming the audio was one of the most highly ‘liked’ comments on the video remix. In another instance, a TikTok creator uploaded a 15-second remix of a popular song that the creator ostensibly made. Several users commented on the video asking the creator if they were indeed the original creator of the remix, and, if so, where they could find the full version of the song. In another example, the comment section of a video that contained a popular audio that had been remixed by several other creators was full of comments from users exclaiming that they finally found the source of the aural meme. As meme culture on TikTok is ephemeral and fast-moving, users do what they can to boost visibility of their original content and locate the source of trending content. Without a strong copyright enforcement system, like that of YouTube, coupled with a problematic automatic attribution system, some creators and users have no choice but to turn to the comments section to assert their original authorship and to ask others “who actually made this??” However, this information seeking behaviour is then complicated by TikTok’s comment filtration system which we observed, is unique to each user and sorted in a distinct way where the most “liked” comment doesn't necessarily rise to the top. Our initial findings suggest that TikTok’s comment section is less straightforward than on other popular social media platforms and future research ought to explore this novelty. References Cyberspace Administration of China. 2017b. Detailed regulations on the administration of internet news service [互联网新闻 信息服务许可管理实施细则]. Retrieved from http://www.cac.gov.cn/2017-05/22/c_1121015789.htm Google. 2019. Content delistings due to copyright. Retrieved from: https://transparencyreport.google.com/copyright/overview?hl=en Han, D. 2018. Proprietary control in cyberspace: three moments of copyright growth in China. ​Media, Culture and Society​, 40(7), 1055–1069. https://doi.org/10.1177/0163443718765929 Hansmann, H., & Santilli, M. 1997. Authors’ and Artists’ Moral Rights: A Comparative Legal and Economic Analysis. ​The Journal of Legal Studies​, 26(1), 95. https://doi.org/10.1086/467990 Keane, M., & Su, G. 2019. When push comes to nudge: A Chinese digital civilisation in-the-making. ​Media International Australia​, 173(1), 3–16. https://doi.org/10.1177/1329878X19876362 Lin, J., & de Kloet, J. 2019. Platformization of the Unlikely Creative Class: Kuaishou and Chinese Digital Cultural Production. ​Social Media and Society​, 5(4). https://doi.org/10.1177/2056305119883430 Meese, J. 2014. It Belongs to the Internet: Animal Images , Attribution Norms and the Politics of Amateur Media Production. ​M/C Journal ​, 17(2), 1–6. Monroy-Hernandez, A., Hill, B. M., Gonzalez-Rivero, J., & Boyd, D. 2011. Computers can’t give credit: How automatic attribution falls short in an online remixing community. Conference on Human Factors in Computing Systems - Proceedings​, 3421–3430. https://doi.org/10.1145/1978942.1979452 Montgomery, L. 2010. ​China’s Creative Industries: Copyright, Social Network Markets and the Business of Culture in a Digital Age​. Cheltenham: Edward Elgar Publishing. Perkel, D. 2016. Share wars: Sharing, theft, and the everyday production of Web 2.0 on DeviantArt. ​First Monday​, 21(6), 1–24. Song, Y., & Wu, Y. 2018. Tracking the viral spread of incivility on social networking sites: The case of cursing in online discussions of Hong Kong–Mainland China conflict. Communication and the Public​, 3(1), 46–61. https://doi.org/10.1177/2057047318756408 TikTok. 2019, December 30. TikTok transparency report. Retrieved from: https://www.tiktok.com/safety/resources/transparency-report?lang=en SPEAKING (IN) PICTURES AND CORPORATE CURATION: COMMENTING CULTURES ON INSTAGRAM Tama Leaver Curtin University Ysabel Gerrard University of Sheffield Introduction As van Dijck (2008) argued more than a decade ago, digitisation and online networks have driven a shift in photography from being largely about memory in an analogue era, to largely about communication in a digital era. Nowhere is that shift more evident than on Instagram, a social media platform which centres on the communicative capacity of visuals (and, more recently, video). Yet, as with all successful social media, Instagram’s platform affordances have developed and changed over time, including affordances which facilitate written ​and ​visual communication in myriad forms. Below, we map the changes Instagram have made in users’ ability to comment on pictures around three main features: (1) the Feed; (2) Direct Messages; and (3) Stories. We then reveal the limits and politics of how Instagram decides who actually gets to use these affordances in exploring the way the platform bans, blocks and ‘shadowbans’ certain users and communities. We trace the evolution of Instagram’s commenting capabilities to show how the platform has helped to redefine what ‘commenting’ means on social media, by enabling (and excluding​) a broader range of communicative responses to posts than most platforms currently allow. We also consider what this means for academic researchers, who are typically not privy to some the core communicative spaces and policies the platform offers. Evolving Comments, Changing Affordances When Instagram launched in 2010, photos were posted to a user’s main ​Feed ​, which other users could view and subsequently like or leave a comment on. The image (usually a photograph) initially had to be taken live (not from a camera’s gallery), and could be aesthetically edited with a series of pre-defined filters. The affordances of early Instagram were thus completely consistent with boyd and Ellison’s (2007) now classic ‘Web 2.0’ era definition of social networks as being driven by a public profile on a specific system (or platform) with each user having a visible network that can itself be traversed by other users. Posting images was the main form of communication (often paired with captions and hashtags), and comments and likes were the main form of interaction for users viewing the content. It was not until 2013 – after Facebook purchased the platform in 2012 (Vaidhyanathan, 2018) – that Instagram rolled out their ​‘Direct’​ messaging service as part of the Instagram app. Direct was, at least, an admission that not all commentary should be publicly visible, allowing users a more private space to engage with one another. In 2015 Direct was revitalized with threaded comments, and over the next few years would, after some delay, include many of the affordances of Stories such as (potentially) disappearing media and including other visual elements, such as animated GIFs. While Instagram has been the most successful platform in popularizing the Stories format, it was initially invented by, and deployed on, Snapchat (Rettberg, 2018). ​Stories ushered in a new type of ​ephemeral​ communication in that Stories disappeared after 24 hours. When Instagram replicated the Stories format, they did so in part to address falling engagement numbers, as users were more and more concerned with posting polished content to their main feed; the impact of Stories was immediate, opening a new space which was again less about aesthetic considerations and more about the immediate commentary and communication (Leaver et al, 2020). The ephemerality of Stories has been key to making this affordance the largest growth space for Instagram. Notably, in 2019 the ability to ‘like’ content in the main Instagram feed has become ​so synonymous​ with Instagram as a metric or popularity based platform, that in 2020 experiments are happening across the globe in removing those ‘likes’, which will probably be permanently removed, ostensibly to make the platform friendlier for commentary once more. Curtailed from Commenting? Bans, Blocks and Shadowbans As we were preparing this abstract, Instagram’s CEO, Adam Mosseri, was accused of lying about how ‘shadowbanning’ works on the platform: the process of secretly hiding or demoting a users’ content (Myers-West, 2018). In an Instagram Live video, Mosseri claimed that shadowbanning is simply ‘not a thing’ (Cook, 2020), contrary to the platform’s own public-facing policies on the de-prioritization of particular forms of content. For example, Instagram says it limits ‘sexually suggestive’ posts from its algorithmically-curated Explore page (Instagram Help Centre, 2020). But at the same time, other forms of shadowbanning might have the capacity to limit online harms; for example, a search for #depression suggests #depressionhelp and #depressionawareness as the next most appropriate tags, directing users to mental health recovery communities instead of potentially harmful content (McCosker and Gerrard, under review). But the lack of transparency around why and how shadowbanning and other forms of content control happen – like blocking users from posting certain comments, or banning their accounts entirely – reminds us how much power platforms have to curate the parameters of acceptability (Gerrard, 2018). Commenting capabilities on Instagram might therefore be framed as a privilege enjoyed by its less controversial userbase, whether or not their controversiality is warranted. Conclusions In 2020, Instagram is a decade old, and over those ten years the platform has become emblematic of broader shifts in the social media landscape. Initially its affordances were consistent with persistent profiles and public or private as a single, binary choice. With the development of Direct messages and ephemeral Stories, Instagram has greatly diversified how users can comment and respond to one another. With more than a billion users, Instagram is a locus of community, commentary and potentially political change. But the controversies around shadowbans and the seemingly inconsistent, or at least vague, application of community guidelines to restrain and remove comments from some, but not others, highlights the need for greater transparency and fuller public disclosure about who is currently able to comment on Instagram, in what capacities, and how that may or may not be restricted in the future. References boyd, d and Ellison, N. 2007. Social Network Sites: Definition, History, and Scholarship. Journal of Computer-Mediated Communication​ 13(1). Cook, J. 2020, February 25. Instagram's CEO Says Shadowbanning Is 'Not A Thing'. That's Not True. ​Huffington Post​. Available at: https://www.huffingtonpost.co.uk/entry/instagram-ceo-shadow-banning-adam-mosseri_u k_5e56359ec5b62e9dc7da552c. Gerrard, Y. 2018. Beyond the Hashtag: Circumventing Content Moderation on Social Media. ​New Media and Society 20​(12): 4492-4511. Instagram Help Centre. 2020. ​Why Are Certain Posts on Instagram Not Appearing in Explore and Hashtag Pages? ​Available at: https://help.instagram.com/613868662393739. Leaver, T, Highfield, T and Abidin, C. 2020. ​Instagram: Visual Social Media Cultures​. Cambridge, UK; Medford, MA, USA: Polity. McCosker, A. and Gerrard, Y. (Under review). Hashtagging Depression on Instagram: Towards a More Inclusive Mental Health Methodology. Myers-West, S. 2018. Censored, Suspended, Shadowbanned: User Interpretations of Content Moderation on Social Media Platforms. ​New Media and Society 20​(11): 4366-4383. Rettberg, J.W. 2018. Snapchat: Phatic Communication and Ephemeral Social Media.” In J. W. Morris and S. Murray. ​Appified: Culture in the Age of Apps ​(pp.188-196). Ann Arbor: University of Michigan Press. Vaidhyanathan, S. 2018. ​Antisocial Media: How Facebook Disconnects Us and Undermines Democracy​. New York: Oxford University Press. van Dijck, J. 2008. “Digital Photography: Communication, Identity, Memory.” ​Visual Communication​ 7(1):57–76.