Mainstream Platforms Research Articles

Fringe discourse networks 1932–2022: a media archaeological approach to (Ex)communication and (De)platforming

ABSTRACT In 1932, the Dutch writer Ernest Michel was banned from publishing with a Catholic publisher for critiquing the Catholic church and Dutch democracy. After his ban, Michel joined Verdinaso, a political organization with strong ties to upcoming National Socialist movements in the Netherlands, where he continued to write, frequently advocating for free speech, and against censorship. In this paper, we will compare the case of Michel with the case of Laurens Buijs, as well as contemporary processes of deplatformization and replatforming. We will discuss the removal of right-wing political actors from mainstream platforms, and analyze their narratives of victimhood and cultural decline, as well as the ‘network of technologies and institutions’, i.e. the ‘discourse networks’ that make far-right and populist political communication possible. We follow a media archaeological approach allowing us to show the continuities in seemingly distant times and seemingly different material and institutional networks, as well as the discontinuities in the development of contemporary media. With this analysis, we aim to contribute to current debates concerning the governance of anti-democratic and right-wing media, and their material and institutional networks.

A Picture Paints a Thousand Words: Perspectives of the Use of Images and Videos of Physical Findings in Virtual OSCE Teaching Sessions.

The COVID-19 pandemic has resulted in medical students' education being disrupted and a new direction of learning towards the online classroom, with students frequently learning to identify clinical signs via online conferencing platforms. Given this shift in student study techniques in the pandemic and post-pandemic era, we set out to analyse the confidence levels of students recognizing clinical signs in patients and the opinions and patterns of resources students would use to build up the knowledge and confidence for their future clinical practice. OSCEazy, a student-led medical education organisation, delivered an online teaching session and disseminated a questionnaire containing ten-point Likert scales, multiple-choice questions and free text options. The majority (over 75%) of respondents reported using digital resources to learn physical examinations. Most respondents were somewhat confident with recognising clinical signs during physical examinations (Median 7, IQR 6-8). Kruskal-Wallis H-test on students' impression of the quality of current OSCE materials showed a statistically significant difference between cohorts (X2(2) = 14.209, p = 0.014). A large proportion of students (98.41%) agreed that an online resources bank would be beneficial for their learning. Wilcoxon rank test showed a statistically significant preference for learning physical examinations using clinical images rather than videos (p = 0.014). A 29% of respondents mentioned the use of physical textbooks as a resource, while online platforms such as OSCE revision websites, YouTube and Google Images had become the mainstream platforms. The findings reported here suggest that there needs to be a greater emphasis on providing online image-based resources to support medical students in learning clinical signs. A resource containing these clinical signs would prove to be of benefit for students to access high-quality self-directed learning to identify and verify clinical signs.

Post-Internet Music: Negotiating Queer Identity in the Digital Era

My paper investigates an electronic music genre that emerged in the 2010s, in conjunction with the rise of attention to identity politics on mainstream platforms. The genre does not have a definite name; however, attempts have been made by critics (see, for example, Waugh 2017) to categorise it under the umbrella term "post-internet music". Such a label encompasses different and often competing sub-genres, all of which nonetheless share an imbrication in internet discourse: these range from Hyperpop, to ‘Deconstructed Club, to ‘Conceptronica’ (Reynolds 2019). As such, the post-internet genre has three distinguishing features: a) many artists operating within it identify both themselves and their music as queer; b) on the sonic side, the genre often comprises complex sound design, loud mixes, a wide stereo field, organic drum samples, pitched-up vocals, and beats that elude conventional time-signatures, so as to sound "deconstructed"; c) the music often makes overt or subtle reference to internet culture, and the digital domain. I seek to place particular attention to the conjuncture between the genre's sonic properties and its ‘queerness’, arguing that the genre is both enabled by, but also enables, internet-mediated identity categories. In this sense, I question what it means to be queer in the contemporary neoliberal era, how this might historically differ from previous elaborations of queerness, and to what extent electronic music - a genre so entrenched in masculinist narratives of technology - can act as a vehicle for counter-normative expression. 

Collective victimhood narratives in far-right communities on Telegram

ABSTRACT Feelings of collective victimhood have been demonstrated to have a strong effect on ingroup bias, outgroup hostility and support for violence. The use of narratives stirring these feelings in far-right communications is especially concerning given their inclusion in the manifestos of several mass killers across Europe and North America. However, scholars still have little knowledge on the reach of such narratives as well as the extent to which major salient events increase attention to collective victimhood messaging among far-right followers. To address these gaps, we analyze the use of collective victimhood narratives on the popular secure instant messaging service, Telegram, which has exploded in popularity in response to mainstream platforms’ attempts to moderate extremist speech. We develop a supervised machine learning algorithm to predict the presence of these discourses in text from over 18.5 million messages that were extracted from 1,870 far-right Telegram channels. We then use these data to test what impact the George Floyd protests and the storming of the US Capitol had on the frequency of collective narrative discussions on far-right Telegram. Our findings suggest that both events coincided with a significant increase in the use of victimhood narratives, thus providing insight into the radicalization process of far-right communities online.

NmTHC: a hybrid error correction method based on a generative neural machine translation model with transfer learning

BackgroundsThe single-pass long reads generated by third-generation sequencing technology exhibit a higher error rate. However, the circular consensus sequencing (CCS) produces shorter reads. Thus, it is effective to manage the error rate of long reads algorithmically with the help of the homologous high-precision and low-cost short reads from the Next Generation Sequencing (NGS) technology.MethodsIn this work, a hybrid error correction method (NmTHC) based on a generative neural machine translation model is proposed to automatically capture discrepancies within the aligned regions of long reads and short reads, as well as the contextual relationships within the long reads themselves for error correction. Akin to natural language sequences, the long read can be regarded as a special “genetic language” and be processed with the idea of generative neural networks. The algorithm builds a sequence-to-sequence(seq2seq) framework with Recurrent Neural Network (RNN) as the core layer. The before and post-corrected long reads are regarded as the sentences in the source and target language of translation, and the alignment information of long reads with short reads is used to create the special corpus for training. The well-trained model can be used to predict the corrected long read.ResultsNmTHC outperforms the latest mainstream hybrid error correction methods on real-world datasets from two mainstream platforms, including PacBio and Nanopore. Our experimental evaluation results demonstrate that NmTHC can align more bases with the reference genome without any segmenting in the six benchmark datasets, proving that it enhances alignment identity without sacrificing any length advantages of long reads.ConclusionConsequently, NmTHC reasonably adopts the generative Neural Machine Translation (NMT) model to transform hybrid error correction tasks into machine translation problems and provides a novel perspective for solving long-read error correction problems with the ideas of Natural Language Processing (NLP). More remarkably, the proposed methodology is sequencing-technology-independent and can produce more precise reads.

Mirroring the inequalities of mainstream music platforms: popularity, revenue, and monetization strategies on Bandcamp

ABSTRACT In the era of digital music streaming, understanding the monetization and popularity dynamics of online audio distribution platforms is crucial for both researchers and music industry professionals. While much of the existing research has focused on mainstream platforms such as Spotify and Apple Music, we study Bandcamp, an alternative marketplace that, among other things, empowers independent artists to upload and sell their music. Leveraging a rich dataset of one million Bandcamp sales, we investigate the distribution of popularity and revenues among artists on the platform. Our analysis reveals a substantial level of inequality, with a small core of musicians concentrating most of the purchases and revenues. Surprisingly, our results also indicate that many artists adopt a monetization strategy that involves devaluing their products, potentially leading to a cherry-picking of songs by consumers. These findings shed light on the challenges faced by alternative music distribution services and emphasize the need for further exploration of a fairer and more sustainable business model for independent artists.

This is how we .win! Capital-building and media manipulation practices on The_Donald

ABSTRACT Scholars have grown increasingly interested in the ways media and communication technologies facilitate the spread of problematic information as well as how their affordances manifest in practice. While we have learned much about the structure and use of popular social media platforms, we have more to learn about less mainstream platforms, and about the ways their usage helps actors amass and wield media power. Accordingly, this paper examines networked political actors’ use of alternative media to generate capital and facilitate the spread of problematic information. Drawing data from two years of research on the pro-Trump internet forum The_Donald following its ban from Reddit, the analysis considers how users develop, debate, and deploy media-related practices, and what role those practices play in shaping the broader political culture in which they exist. In addition to gleaning insights from sustained participant-observation in the forums, a content analysis of activist meta-discourse examines the technological structure and affordances of The_Donald as well as the most salient themes and broader discursive patterns, focusing specifically on those aspects of the forum that pertain to practices of manipulation and expressions of media power. This analysis shows how the structure and culture of the forum enable and encourage manipulative media practices. Furthermore, it demonstrates how the unique combination of affordances and political opportunities available to actors allowed them to generate and wield novel forms of networked media capital.

The Research of Collaborative System of Remote Sensing Monitoring Based on Bimodal Cloud

Abstract. Cloud service is based on cloud computing, Offering a On-Demand service to every terminal equipment of computing resource pool. This paper designed and developed a coordinated operating system based on bimodal cloud. This system is taken mutual scheduling mechanism into account, which is capable of storing massive amounts of heterogeneous remote sensing data and provides fast indexing of data based on various characteristics, integrated Satellite transit forecast, DOM Produce, coordinated change information extraction and results sharing based on Nginx load balancing, in addition, the system designed two layer security system to ensure the safety of data results.The "YunYao" geographic information service rendering engine built on the dual-state cloud platform significantly outperforms mainstream platforms in the same testing environment. Its rendering speed surpasses ArcGIS Desktop by more than two times, exceeds GeoServer by more than four times, and is over seven times faster than ArcGIS Server. Remote sensing practitioners can quickly and conveniently utilize this system, while providing convenient functionalities that enable remote sensing scientists to independently conduct scientific research and development using this system. Experimentation and practice shows that this system simplified routine work flow, improved work efficiency, has a important reference meaning to remote sensing monitoring.

A study on satisfaction evaluation of Chinese mainstream short video platforms based on grounded theory and CRITIC-VIKOR

In recent years, Chinese short video platforms have experienced vigorous development, accompanied by increasing expectations and demands from users. This study aims to explore the factors influencing user satisfaction on mainstream Chinese short video platforms and provide a scientific and objective evaluation framework to support the enhancement of user satisfaction and the development of short video platforms. Through a combination of qualitative and quantitative research methods, multiple mainstream Chinese short video platforms were evaluated and analyzed. Firstly, semi-structured interviews with users were conducted using Grounded Theory to delve into the key factors shaping users' expectations, needs, and satisfaction towards short video platforms. Secondly, the CRITIC-VIKOR method was employed to assign comprehensive weights to various factors and to evaluate the satisfaction levels of the mainstream platforms. The study revealed that the core categories affecting user satisfaction include content quality and interaction, trust and values, and user experience. The weighted values of the main categories are as follows: interface and interaction design 0.124, personalized experience 0.115, platform stability and performance 0.075, privacy and security 0.133, user service and communication 0.060, social impact and values 0.124, content quality and diversity 0.088, social interaction 0.094, and advertising experience 0.186. Furthermore, the satisfaction evaluation of mainstream short video platforms indicated that bilibili platform garnered the highest user satisfaction among surveyed users. This study provides specific directions for improving user experience and enhancing user satisfaction for short video platforms, while also offering a evaluation framework based on Grounded Theory and CRITIC-VIKOR method for similar studies, thus expanding the theoretical and practical fields of user satisfaction research.

Mapping the Landscape of Independent Food Delivery Platforms in the United States

Beyond the well-known giants like Uber Eats and DoorDash, there are hundreds of independent food delivery platforms in the United States. However, little is known about the sociotechnical landscape of these "indie'' platforms. In this paper, we analyzed these platforms to understand why they were created, how they operate, and what technologies they use. We collected data on 495 indie platforms and detailed survey responses from 29 platforms. We found that personalized, timely service is a central value of indie platforms, as is a sense of responsibility to the local community they serve. Indie platforms are motivated to provide fair rates for restaurants and couriers. These alternative business practices differentiate them from mainstream platforms. Though indie platforms have plans to expand, a lack of customizability in off-the-shelf software prevents independent platforms from personalizing services for their local communities. We show that these platforms are a widespread and longstanding fixture of the food delivery market. We illustrate the diversity of motivations and values to explain why a one-size-fits-all support is insufficient, and we discuss the siloing of technology that inhibits platforms' growth. Through these insights, we aim to promote future HCI research into the potential development of public-interest technologies for local food delivery.

Affective, defective, and infective narratives on social media about nuclear energy and atomic conflict during the 2022 Italian electoral campaign

In the digital age, poor public communication catalyzes the spread of disinformation within public opinion. Anyone can produce political content that can reach a global audience, and social media has become a vital tool for political leaders to convey messages to the electorate. The 2022 Italian election campaign has seen the term “nuclear” debated with two different declinations: on the one hand, regarding nuclear energy for civilian use, and on the other hand, regarding the fear of an escalation of the conflict in Ukraine and the use of atomic weapons. This research aims to analyze the social media debate by exploring multiplatform dynamics to qualitatively identify and analyze the connections between social media platforms that we have termed Bridges, a concept drawn from Transmedia Theory to describe the narrative relationship between platforms. The methodological approach will follow an explanatory sequential design that will rely on digital methods to identify connections between platforms (bridges) and then apply an exploratory qualitative approach to enrich the data and capture the nuances of the debate. As expected, we found polarized positions and fragmentation on both issues of civilian nuclear energy and the atomic conflict narrative. Primary evidence shows bridges spreading affective, defective, and infective content across platforms in a multifaceted social media ecosystem. Affective refers to rhetoric that appeals to people’s feelings. Defective means the discussion that brings attention to hyper-partisan news channels, fake news, and misinformation. Infective means bridges with below-the-radar platforms, niche channels, or pseudo-information channels. They use bridges with mainstream platforms to gain the potential to go viral. The paper highlights the importance of cross-platform and interdisciplinary approaches to addressing disinformation in a media ecosystem where social media plays an increasing role in a country’s democratic dynamics.

Modular formation of in vitro tumor models for oncological research/therapeutic drug screening.

In recognition of the lethal nature of cancer, extensive efforts have been made to understand the mechanistic causation while identifying the effective therapy modality in hope to eradicate cancerous cells with minimal damage to healthy cells. In search of such effective therapeutics, establishing pathophysiologically relevant in vitro models would be of importance in empowering our capabilities of truly identifying those potent ones with significantly reduction of the preclinical periods for rapid translation. In this regard, wealthy progresses have been achieved over past decades in establishing various in vitro and in vivo tumor models. Ideally, the tumor models should maximally recapture the key pathophysiological attributes of their native counterparts. Many of the current models have demonstrated their utilities but also showed some noticeable limitations. This book chapter will briefly review some of the mainstream platforms for in vitro tumor models followed by detailed elaboration on the modular strategies to form in vitro tumor models with complex structures and spatial organization of cellular components. Clearly, with the ability to modulate the building modules it becomes a new trend to form in vitro tumor models following a bottom-up approach, which offers a high flexibility to satisfy the needs for pathophysiological study, anticancer drug screening or design of personalized treatment.

Dynamics of Social Media Engagement in Pakistan: A Comprehensive Analysis of User Trends Across Platforms

Abstract The purpose of this research paper is to conducts a comprehensive examination of social media engagement in Pakistan, focusing on user trends across diverse platforms. [1]A longitudinal observational research design was adopted to capture temporal variations in user interactions on major social media platforms. The data collection process involved sourcing monthly engagement metrics from publicly available platform analytics, ensuring accuracy and reliability. The analysis begins with Facebook, revealing distinctive fluctuations in engagement percentages over the observed months. Peaks in November 2022 and subsequent recoveries underscore the impact of seasonality, content dynamics, and platform updates on user behavior. Twitter, as a microblogging platform, maintains a consistent but comparatively lower level of engagement, resiliently serving audiences seeking real-time and concise content. Visual-centric platforms like YouTube and Instagram exhibit dynamic patterns, with YouTube's fluctuating percentages indicating a diverse content landscape and an uptick in Instagram engagement signaling evolving user preferences for visually-driven experiences. Beyond mainstream platforms, the study extends its focus to niche audiences on platforms such as Pinterest, LinkedIn, Reddit, and others, revealing the coexistence of platforms catering to specific interests. the findings contribute to a distinctive understanding of user behavior, uncovering the impact of various factors on engagement percentages across different social media platforms in Pakistan. Future research endeavors can build upon these insights, exploring additional dimensions of social media engagement and it's evolving trends within the digital landscape of Pakistan.

Tales of Two Channels: Digital Advertising Performance Between AI Recommendation and User Subscription Channels

Although in-feed advertising is popular on mainstream platforms, academic research on it is limited. Platforms typically deliver organic content through two methods: subscription by users or recommendation by artificial intelligence. However, little is known about the ad performance between these two channels. This research examines how the performance of in-feed ads, in terms of click-through rates and conversion rates, differs between subscription and recommendation channels and whether these effects are mediated by ad intrusiveness and moderated by ad attributes. Two ad attributes are investigated: ad appeal (informational vs. emotional) and ad link (direct vs. indirect). Study 1 finds that the recommendation channel generates higher click-through rates but lower conversion rates than the subscription channel, and these effects are amplified by informational ad appeal and direct ad links. Study 2 explores channel differences, revealing that the recommendation channel yields less source credibility and content control, reducing consumer engagement with organic content. Studies 3 and 4 validate the mediating role of ad intrusiveness and rule out ad recognition as an alternative explanation. Study 5 uses eye-tracking technology to show that the recommendation channel has lower content engagement, lower ad intrusiveness, and greater ad interest.

Between alternative and traditional social platforms: the case of gab in exploring the narratives on the pandemic and vaccines.

The phenomenon of deplatforming intended as the removal of social media accounts because of breaking rules on mainstream platforms such as Facebook, Twitter, YouTube, and Instagram recently increased due to new terms and conditions of use of digital media, and new alternative social media platforms emerged and presented themselves as protectors of freedom expression. In this way, it becomes interesting to understand better the context of these platforms' so-called web suburbs that consist in those digital places that ≪host what we can generally call "subcultures," including fandoms, religious sects, political extremists, and subcultures≫. Since April 2020, Gab can be considered the most widespread alternative platform in Western countries, with twenty million users daily, born as Twitter and Facebook alternative social media. The alternative social media platforms are intended as other connection services between users, which is halfway between a social media and a discussion forum born to boycott the censorship actions of the main social media platforms (Meta Group, Twitter, etc.) and celebrate free speech even on controversial positions. How are sensitive topics, such as the one that concerns the skepticism related to the approvals of vaccines during the pandemic, addressed on the alternative social media platform compared to how they are dealt with on the mainstream social media platforms? This explorative work wonders about the users' points of view on vaccine concerns and the relevant differences between Gab and Facebook in addressing this topic. The empirical part of this work has been set starting from the dataset composed of Gab and Facebook content posted between March 2020 and July 2021. The posts were extracted with web scraping techniques (for Gab) and proprietary data tools (for Facebook), querying the keywords: vaccine, vaccines, anti-vax (no-vax), Covid, Covid-19, coronavirus. The collection procedure considered the different platforms' structure and their different organization of the interaction spaces. The population consisted of 8000 English writers' posts, from which 2000 posts with the highest interaction value were extracted. The dataset was analyzed using Topic Modeling, Factor, and Classification Analysis techniques. Our work's methodological output deals with comparing these social media platforms, bearing in mind their ontological objects and their algorithms' role. From the analysis emerged the differences and similarities of the social media platforms in terms of the type of content published, rates of involvement, sources of information, and directions of the considered speech. These differences have been duly highlighted by three clusters related to discourse orientation and communication approach: Conflict of views, Emotional externalization, Recommendation and practices. In addition to the type of communication and information circulating on a powerful platform such as Gab, the results help us understand the different narratives promoted on the two social media platforms and their role in the possible promotion of the same sentiment, opinions, and ideological polarization.

Comparing the #StopTheSteal Movement across Multiple Platforms: Differentiating Discourse on Facebook, Twitter, and Parler

Given that political groups are dispersed across platforms, resulting in different discourses, there is a need for more studies comparing communication across platforms. In this study, we compared posts about #StopTheSteal from three social media platforms after the 2020 US Presidential election and preceding the January 6 Capitol Riot. To do so, we utilized Snow and Benford’s typology of social movement frames—diagnostic, prognostic, and motivational frames—in the context of far-right movements and an additional frame device: violence cues. This study focused on the following three social media platforms: Facebook, Twitter, and Parler. We built three corpora of social media data: 26,093 Facebook posts, 248,643 tweets, and 400,600 Parler posts. Using Bidirectional Encoder Representations from Transformers (BERT) classifiers, dictionary methods, and qualitative text analysis, we find that the use of these frames varies by platform, with users on the alt-tech platform Parler using violence cues such as “smash” and “combat,” suggesting a greater call to action relative to the mainstream platforms.

Spillover of Antisocial Behavior from Fringe Platforms: The Unintended Consequences of Community Banning

Online platforms face pressure to keep their communities civil and respectful. Thus, banning problematic online communities from mainstream platforms is often met with enthusiastic public reactions. However, this policy can lead users to migrate to alternative fringe platforms with lower moderation standards and may reinforce antisocial behaviors. As users of these communities often remain co-active across mainstream and fringe platforms, antisocial behaviors may spill over onto the mainstream platform. We study this possible spillover by analyzing 70,000 users from three banned communities that migrated to fringe platforms: r/The_Donald, r/GenderCritical, and r/Incels. Using a difference-in-differences design, we contrast co-active users with matched counterparts to estimate the causal effect of fringe platform participation on users' antisocial behavior on Reddit. Our results show that participating in the fringe communities increases users' toxicity on Reddit (as measured by Perspective API) and involvement with subreddits similar to the banned community---which often also breach platform norms. The effect intensifies with time and exposure to the fringe platform. In short, we find evidence for a spillover of antisocial behavior from fringe platforms onto Reddit via co-participation.

The Internet’s Town Square? A Critical Discourse Analysis of Parler’s “Past Imaginary”

The discursive construction of sociotechnical imaginaries by the leaders of platform companies can help legitimate their platforms, shaping how they are perceived and ultimately regulated. Scholars have identified the construction of “future imaginaries” by large platform companies such as Meta—but do smaller platforms also seek to construct imaginaries, and if so, what form do they take? In this article we undertake a critical discourse analysis of statements by John Matze, co-founder and CEO of the fringe social media platform Parler, that garnered media coverage in 2020. Parler gained significant popularity among US right-wing users during 2020, before it was removed from Apple and Google’s app stores in January 2021 following the riot at the US Capitol. Using Van Leeuwen’s framework for discursive legitimation, we analyze a curated dataset of 186 news articles to identify the legitimating themes that Matze invoked in media coverage of Parler in 2020. We find that Matze foregrounded free expression, and with it the vision of Parler as a “town square,” which can be seen as an attempt to legitimate the fledgling platform. However, this discursive legitimation must be understood in the context of Parler’s base of predominantly US right-wing users, many of whom turned to Parler because of the perceived “bias” and “censorship” of mainstream platforms. We argue that, in contrast to the future imaginaries constructed for large platform companies such as Meta, Matze’s discursive strategy constructed an imaginary that was fundamentally retrograde. Parler’s “past imaginary” resembles efforts by far-right groups to justify and legitimate hate speech in increasingly platformized societies.

THE TOXIC TURN? CONCEPTUAL AND METHODOLOGICAL ADVANCES ON PROBLEMATIC CONTENTS ON SOCIAL MEDIA

The ‘toxic turn’ in social media platforms continues unabated. Hate speech, mis- and disinformation, misogynistic and racist speech, images, memes and videos are all far too common on social media platforms and more broadly on the internet. While the diminishing popularity of populist politicians led to hopes for less social toxicity, the Covid-19 pandemic introduced new and more complex dimensions. Tensions have emerged around what constitutes problematic content and who gets to define it. Co-regulation models, such as for example the EC Code of Conduct against Illegal Hate Speech, focus on the legality of certain types of contents, while leaving other categories of problematic contents to be defined by platforms. In parallel, the social media ecosystem became more diverse, as new platforms with hands off moderation policies attracted users who felt too constrained by the policies of mainstream platforms. The proposed panel examines this complex and dynamic landscape by problematizing what is understood as toxic, deplatformed, removable and in general problematic content on platforms with the aim to probe the boundaries of what is constituted as acceptable discourse on platforms and to map its implications. In particular, this panel discusses the broad definition of ‘problematic content’ employed by social media platforms, a catch-all term that cuts across hate speech and propaganda, including more politically topical content such as mal-, mis-, and disinformation, hyperpartisan and polarising content, but also abusive, misogynistic, racist, and homophobic discourse. The term is also employed to refer to spam and content that infringes upon the Terms of Service or the Community Standards of social media platforms. As such, it is a broad category that resists a narrower classification given the operational scope of its use. Defining what constitutes problematic content is a key operation of platform content moderation policies but is also the subject of intense debates (de Gregorio, 2020; Gillespie, 2018; Gillespie et al., 2020; Gorwa et al., 2020). The panel interrogates the many definitions and applications of problematic content on social media platforms and applications through an empirically informed lens and focusing on deleted contents, complex mixed narratives, and grey areas, including hidden misinformation on voice applications. Problematic Content according to Twitter Compliance API presents ongoing work on the Twitter Compliance API and the Compliance Firehose, which allow researchers to identify content that has been deleted, deactivated, protected, or suspended from Twitter, a proxy for problematic content. In Multi-Part Narratives on Telegram Siapera presents ongoing research that probes the intersection between Covid-19 scepticism, far right and other political narratives in vaccine hesitant groups on Telegram. The third contribution, What if Bill Gates really is evil, people? Investigating the infodemic’s grey areas discusses the conceptual and methodological definitions of problematic content in relation to work on anti-vax and other conspiratorial narratives on Instagram and on Twitter. The fourth contribution, Misinformation and other Harmful Content in Third-Party Voice Applications focuses on problematic content that is yet to be identified on voice applications such as personal assistants. The article addresses the methodological challenges of identifying and defining such contents on applications that have currently no content moderation policies. All contributions foreground the difficulties and costs of identifying and dealing with problematic contents on social media. The panel fits with theme of decolonization in two ways: firstly, because it is concerned with the tensions around how toxic/problematic contents are defined and who gets to define them; and secondly, because of its focus on neo-colonial discourses or justifications for colonialism in both narratives hosted by platforms and in platforms’ attempts to regulate content. As some narratives are flagged for removal by social platforms, they also raise the question of who is deciding and what does problematic content mean, with far right discourses exploiting this tension and ironically denouncing any attempt to regulate the public discourse as ideological enforcement and justification for (neo)colonial practices performed by social media platforms. From this perspective, platforms' own claims about what constitutes acceptable content is uncomfortably close to colonial narratives of civilised discourse and brings to the fore the potential for neo-colonial narratives and practices in digital spaces.

Cross-Platform Reactions to the Post-January 6 Deplatforming

We study changes in social media usage following the ‘Great Deplatforming’ inthe aftermath of the 6 January 2021 attack on the US Capitol. Following theattack, several major platforms banned thousands of accounts, ostensibly tolimit misinformation about voter fraud and suppress calls for violence. At thesame time, alternative platforms like Gab, BitChute, and Parler welcomed thesedeplatformed individuals. We identify three key patterns: First, in studyingthe platforms that emerged among users seeking alternative spaces, we see highfrequencies of users bridging these communities announcing their intent to joinnon-mainstream platforms to their audiences on mainstream platforms. Second, focusing on platforms that were created to be alternative, anti-censorshipspaces, deplatforming preceded a sustained increase in engagement with Gabacross Twitter, Reddit, and Google search, while Parler saw a steep decline inengagement. Third, examining the language in these spaces, toxic discourseincreased briefly on Reddit and Twitter but returned to normal after the deplatforming, while Gab became more toxic. These results suggest that whiledeplatforming may precede a reduction in targeted discussions within a specific platform, it can incentivize users to seek alternative platforms where thesediscussions are less regulated and often more extreme.As these alternative spaces are often more political and extreme than their mainstream counterparts, deplatforming may drive single-platform improvements at the expense of the larger information ecosystem.