Previous studies show that random tweet collections that include more than one hashtag had relatively low rate of unavailable tweets while political related datasets have a higher rate of tweet decay (Almuhimedi et al., 2013; Bastos, 2021; Bhattacharya & Ganguly, 2016; McCammon, 2022; Zubiaga, 2018). For example, Zubiaga’s (2018) study indicates that 81.4% of their 30 randomly selected real-world events datasets remained available after 4 years, while Bastos’ (2021) study shows that only 67% of Brexit debate related tweets were available after the same amount of time. Our preliminary study looks at the #BlackLivesMatter discussion on Twitter and we find that only 63% tweets remain available after 2 years, which is significantly higher compared to the previous studies.

This preliminary work adds to the existing literature in two keyways. First, we broaden the kinds of discussion spaces where information decay has been studied by focusing on #BlackLivesMatter (hereafter, BLM), which in the U.S. has become a highly politicized movement (Stewart et al., 2018). Second, to our best knowledge, this is the first study looking at social movement tweets since Musk took over and it may highlight how the landscape on Twitter has shifted.

Solidarity has been cited as a necessary prerequisite for transformational structural change and therefore contains revolutionary potential (Featherstone, 2012). This paper examines the role and evolution of mediated solidarities, which have become increasingly central to an analysis of social movements with the advent of participatory technologies, by drawing on data from a project on anti-Islamophobic counter-narratives.

Online platforms have the affordances to contest Islamophobic hate speech as demonstrated by the dynamics of #stopIslam following the Brussels terror attack, 2016. In this instance, the hashtag gained its prominence through the contestations of users who sought to question, critique and undermine its original message (reference redacted). However, research has also shown the limitations of social media for online activism, in particular for creating meaningful debates or change (Schradie, 2019).

This paper examines data from a large-scale study that used methods of computational, quantitative, and qualitative analysis to examine the dynamics of discourse about Muslims on Twitter in the case of Brexit, the Christchurch terror attack and Covid. We will examine whether the high incidence of solidarity discourses in this dataset are limited to acts of counter-speech (and other acts of weak solidarity) or if they contribute to sustainable counter-narratives that have implications for wider discursive formations related to Islam. Rather than reinforce existing binary arguments regarding the potentials and limitations of Twitter as a platform for solidarity, we wish to demonstrate the contradictory dynamics of the solidarities that arise from the logics of Twitter which relies on and produces these entanglements.

Using survey data from a 2022 survey of fans that was distributed on Tumblr between February 22 and March 21, 2022, this paper speculatively maps the network of Tumblr. Tumblr is home to fandoms of all kinds, acting as a space where fans can gather, discuss theories, produce fan texts and media, and interact with fanworks, making them one of the key distinctive communities that use the site and a suitable community to investigate the shape of the network. First, we analyze the prevalence of particular demographic answers from the survey over time to find points at which a large number of responses have similar identities. Second, we use the baseline probability of any given answer within our data set to examine times when it becomes disproportionately prevalent compared to elsewhere in the data. Through looking at these correlations between time and probability in specific demographic answers, we can identify moments when the survey was traveling through a homophilic network within the platform, and therefore extract information about how homophily works on this platform. By mapping Tumblr through these survey homophiles, we can gain a greater understanding of how people gather and interact on the platform. This has implications both for questions of community and subcultural belonging, but also issues like the spread of mis- and disinformation.

This research intends to trace, examine and appraise the political economic architecture of social media manipulation using an interdisciplinary, multi-method approach. Our empirical study focuses on a broad category of social media influencers (i.e., microcelebrities, content creators, interest pages) engaged in manipulative work in the 2022 Philippine General Election given its recent history of endemic disinformation in politics, industrialized disinformation operations, and clandestine influencer engagement. We investigate influencers’ participation in covert political campaigning from the lens of political economy in three stages. First, we interrogate the political and economic conditions of disinformation work performed by influencers through digital ethnography and key informant interviews. Second, we map the influencers in their performance of social media manipulation work entangled within large socio-technical networks using computational methods. Thirdly, we integrate these political economic contexts on the ground and online to build an economic model that would estimate the true cost of disinformation campaigns in the Philippines. Our research covers the period of October 2021 to May 2022 across four major social media platforms in the Philippines, Facebook, YouTube, Twitter and TikTok. By integrating qualitative social science, computational communication research, and economic modeling, the research intends to determine the scale and scope of the obscure political relations and economic transactions among political clients, social media influencers, and technology platforms that facilitate social media manipulation.