No abstract

Facebook research has proliferated during recent years. However, since November 2017, Facebook has introduced a new limitation on the maximum amount of page posts retrievable through their Graph application programming interface, while there is limited documentation on how these posts are selected. This paper compares two datasets of the same Facebook page, a full dataset obtained before the introduction of the limitation and a partial dataset obtained after, and employs bootstrapping technique to assess the bias caused by the new limitation. This paper demonstrates that posts with high user engagement, Photo posts and Video posts, are over-represented, while Link posts are underrepresented. Top-term analysis reveals that there are significant differences in the most prominent terms between the full and partial dataset. This paper also reverse engineered the new application programming interface's ranking algorithm to identify the features of a post that would affect its odds of being selected. Sentiment analysis reveals that there are significant differences in the sentiment word usage between the selected and non-selected posts. This paper has significant implications for the representativeness of research that use Facebook page data collected after the introduction of the limitation.

Online messaging app Telegram has increased in popularity in recent years surpassing Twitter and Snapchat by the number of active monthly users in late 2020. The messenger has also been crucial to protest movements in several countries in 2019-2020, including Belarus, Russia and Hong Kong. Yet, to date only few studies examined online activities on Telegram and none have analyzed the platform with regard to the protest mobilization. In the present study, we address the existing gap by examining Telegram-based activities related to the 2019 protests in Hong Kong. With this paper we aim to provide an example of methodological tools that can be used to study protest mobilization and coordination on Telegram. We also contribute to the research on computational text analysis in Cantonese—one of the low-resource Asian languages,—as well as to the scholarship on Hong Kong protests and research on social media-based protest mobilization in general. For that, we rely on the data collected through Telegram’s API and a combination of network analysis and computational text analysis. We find that the Telegram-based network was cohesive ensuring efficient spread of protest-related information. Content spread through Telegram predominantly concerned discussions of future actions and protest-related on-site information (i.e., police presence in certain areas). We find that the Telegram network was dominated by different actors each month of the observation suggesting the absence of one single leader. Further, traditional protest leaders—those prominent during the 2014 Umbrella Movement,—such as media and civic organisations were less prominent in the network than local communities. Finally, we observe a cooldown in the level of Telegram activity after the enactment of the harsh National Security Law in July 2020. Further investigation is necessary to assess the persistence of this effect in a long-term perspective.

Drawing on data from Facebook, this article examines how elements of nationalism discourse were invoked by political actors to advance their agenda. In this paper, a novel mixed-method approach is introduced. The analysis begins with the quantitative phase, and topic modelling is used to identify the recurring themes in corpus. A topic network is generated based on the semantic association and centrality measures from social network analysis are used to identify the core topics in the discourse. In the qualitative phase, texts from the core topics are analysed discursively. The findings reveal that Hong Kong nationalism discourse includes three frames: the threat frame that constructs the overarching narrative of China Threat, the identity frame that engages with the debate on localism and nationalism and the action frame that discusses the actions to be taken in response to the threats.

News consumption exhibits an increasing shift towards online sources, which bring platforms such as YouTube more into focus. Thus, the distribution of politically loaded news is easier, receives more attention, but also raises the concern of forming isolated ideological communities. Understanding how such news is communicated and received is becoming increasingly important. To expand our understanding in this domain, we apply a linguistic temporal trajectory analysis to analyze sentiment patterns in English-language videos from news channels on YouTube. We examine transcripts from videos distributed through eight channels with pro-left and pro-right political leanings. Using unsupervised clustering, we identify seven different sentiment patterns in the transcripts. We found that the use of two sentiment patterns differed significantly depending on political leaning. Furthermore, we used predictive models to examine how different sentiment patterns relate to video popularity and if they differ depending on the channel's political leaning. No clear relations between sentiment patterns and popularity were found. However, results indicate, that videos from pro-right news channels are more popular and that a negative sentiment further increases that popularity, when sentiments are averaged for each video.

Growing concerns about “online harm” and “duty of care” fuel debate about how best to regulate and moderate “troubling content” on social media. This has become a pressing issue in relation to the potential application of media guidelines to online discussion of death by suicide—discussion which is troubling because it is often transgressive and contested. Drawing on an innovative mixed‐method analysis of a large‐scale Twitter dataset, this article explores in depth, for the first time, the complexities of applying existing media guidelines on reporting death by suicide to online contexts. By focusing on five highly publicised deaths, it illustrates the limits of this translation but also the significance of empathy (its presence and absence) in online accounts of these deaths. The multi‐relational and politicised nature of empathy, and the polarised nature of Twitter debate, suggests that we need to step back from calls for the automatic application of guidelines produced in a pre‐digital time to understand more about the sociocultural context of how suicide is discussed on social media. This stepping back matters because social media is now a key part of how lives and deaths are deemed grievable and deserving of our attention.

We examine Telegram-based activities related to the 2019 protests in Hong Kong thus presenting the first study of a large Telegram-aided protest movement. We contribute to both - scholarship on Hong Kongese protests and research on social media-based protest mobilization. For that, we rely on the data collected through Telegram’s API and a combination of network analysis and computational text analysis. We find that the Telegram-based network was cohesive ensuring the efficient spread of protest-related information. Content spread through Telegram predominantly concerned discussions of future actions and protest-related on-site information (i.e., police presence in certain areas). We find that the Telegram network was dominated by different actors each month of the observation suggesting the absence of one single leader. Further, traditional protest leaders - those prominent during the 2014 Umbrella Movement, - such as media and civic organisations were less prominent in the network than local communities. Finally, we observe a cooldown in the level of Telegram activity after the enactment of the harsh National Security Law in July 2020. Further investigation is necessary to assess the persistence of this effect in a long-term perspective.

Nationalism is often associated with xenophobia and isolationism in academic literature. The negative image of nationalism has been further strengthened by the electoral success of far‐right political figures across the world. However, treating all nationalism as a uniformly negative phenomenon risks over‐simplification, as nationalism might manifest differently given different social context and rhetorical resources available. Taking Hong Kong as a case, this paper theorises Hong Kong as a stateless nation and examines the alleged negative association of nationalism. It moves beyond the traditional ‘Hong Kong vis‐a‐vis China’ framework and explores the relationship between Hong Kong nationalists and non‐Chinese international actors. Drawing on data from major Hong Kong political parties' Facebook page, this paper shows that Hong Kong nationalism exhibits a high level of internationalism in both inward and outward dimensions, theorised, respectively, as the willingness to accept foreign influence and to invite international cooperation, and therefore offers a nuanced understanding about the relationship between nationalism, xenophobia and isolationism.