Uptake, polymorphism, and memetic construction within #HimToo

Rathnayake, Chamil (2020) Uptake, polymorphism, and memetic construction within #HimToo. In: 11th International Conference on Social Media & Society, 2020-07-22 - 2020-07-24.

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    Background: The notion of ‘Media events’— grand occasions, such as contests of politics or sports, charismatic missions, and the rites of passage of the great that are televised as they take place, gathering attention universally and simultaneously (Dayan, 2010)— has been applied in many different contexts. In Media Events, Dayan and Katz (1992) frame the notion as a television genre that interrupts normal flows of broadcasting as well as the daily routines of viewers, commanding attention to a ‘ceremonial core’. Sonnevend (2018) argues that Media Events (Dayan & Katz, 1992) has been unfairly labelled a ‘television book’ perhaps due to the fact that the specific focus on live television limited its application across different types of media. Sonnevend argues that such application can be done without compromising its basic tenets. However, scholars have highlighted the need for revisiting media events in the context of digital media. As Couldry and Hepp (2018) note, “what matters is to know whether and why ‘media events’ remain a ‘live’ concept for researching the broadest social and political consequences of media and communications infrastructures and institutions” (p.115). Couldry and Hepp argue that it does remain live, yet they point to the complexity of media events in contexts in which they permeate digital media. Objective: This study conducts a network analysis of the Twitter hashtag #HimToo to initiate development of a notion of networked events as a platform-oriented conception of media events. The study examines whether #HimToo, as a networked event constructed via Twitter uptake, shows a consistent focus (a “centre”) across time frames. Methods: Empirical analysis was conducted based on the argument that #HimToo, a relatively shortlived Twitter hashtag which emerged in response to Brett Kavanaugh hearing (Boyle & Rathnayake, 2019), can be seen as a networked event allowed by Twitter affordances. The ‘broadcast core’ of the event was the live hearing on the 27th of September, 2018. From a strict media events perspective, the live hearing can be seen as a media event in which the broadcast audience does not play a significant role in the construction of the narrative. The hashtag #HimToo was chosen for analysis as it emerged focusing specifically on the Kavanaugh appointment while #MeToo had already sustained for approximately 12 months. The intensity of tweeting was observed and data was gathered covering two periods that showed significant activity level. First, there was a substantial increase in Twitter activity on the day of the hearing. Data collection was started eight days after the broadcast testimony. The API returned a dataset of 112,169 tweets covering the period between 25th of September and 5th of October (T1). As there was a considerable rise in the number of tweets containing #HimToo on the 9th and 10th of April, another sample was obtained for analysis. This second dataset included 250,000 tweets and was obtained on the 12th of December (T2). As the primary emphasis was uptake via retweets, original tweets, @replies, and mentions were removed from analysis. Results: Figure 1 (top) shows a #HimToo retweet network for the first period (T1). This retweet network included 83530 messages (represented by edges) sent by 55562 users (represented by nodes). Partitions within this network were identified by using the community detection algorithm developed by Blondel, Guillaume, Lambiotte, and Lefebvre (2008). A modularity value of 0.521 indicated that the #HimToo retweet network was not highly fragmented. Results also showed that there are 483 communities (clusters) in the network. However, the majority of retweets (51.9% nodes included in the largest component) originated from users taking up tweets sent by the conservative political figure Candace Owens who gathered more than 50% of retweeting activity between 25th of September and 5th of October 2018. Figure 1 (bottom left) shows the partition lead by Candace Owens. As shown in the frequency distribution (Figure 1- bottom right), while Candace Owens attracted more than 50% of users in the network, the rest of the activity was scattered across 482 small clusters.