A Link Communities Analysis of the UK Instagram Covid-19 Searchable Metadiscourse

Many studies focus on utterances included within specific hashtags. This approach does not adequately acknowledge the fact that social media discourse is distributed across a wide range of hashtags. To assess such ‘width of discourse’, we examine the extent to which dominant hashtags in the UK Covid-19 Instagram discourse connect with hashtags related to different aspects of social life. A network of Instagram hashtags (31,742 nodes and 107,367 edges) constructed using #nhsheroes, #captaintommoore, and #carehomes as key access points was analysed. Results showed that top nodes in the network representing these and other topics related to the pandemic are highly intertwined. Moreover, results revealed that despite connections among each other, hubs in this network tend to connect more with low degree frames, connecting secondary hashtags to the Covid-19 searchable discourse. Results revealed that a diverse set of local structures consisting of secondary frames are nested within pandemic related communities.

[1]  Sune Lehmann,et al.  Link communities reveal multiscale complexity in networks , 2009, Nature.

[2]  K. Hyland,et al.  Metadiscourse: Exploring Interaction in Writing , 2005 .

[3]  A. Bruns,et al.  The use of Twitter hashtags in the formation of ad hoc publics , 2011 .

[4]  Zizi Papacharissi Affective publics and structures of storytelling: sentiment, events and mediality , 2016 .

[5]  D. Boyd Social Network Sites as Networked Publics: Affordances, Dynamics, and Implications , 2010 .

[6]  Jeffrey Layne Blevins,et al.  Tweeting for social justice in #Ferguson: Affective discourse in Twitter hashtags , 2019, New Media Soc..

[7]  Anthony M. Limperos,et al.  Uses and Grats 2.0: New Gratifications for New Media , 2013 .

[8]  Daniel D. Suthers,et al.  Twitter Issue Response Hashtags as Affordances for Momentary Connectedness , 2017, SMSociety.

[9]  Pavel Tomancak,et al.  linkcomm: an R package for the generation, visualization, and analysis of link communities in networks of arbitrary size and type , 2011, Bioinform..

[10]  John Jones,et al.  Switching in Twitter’s Hashtagged Exchanges , 2014 .

[11]  Michele Zappavigna Enacting identity in microblogging through ambient affiliation , 2014 .

[12]  Leen D'Haenens,et al.  From #selfie to #edgy. Hashtag networks and images associated with the hashtag #jews on Instagram , 2019, Telematics Informatics.

[13]  Daniela Jaramillo-Dent,et al.  #MigrantCaravan: The border wall and the establishment of otherness on Instagram , 2019, New Media Soc..

[14]  Mark Newman,et al.  Networks: An Introduction , 2010 .

[15]  A. Hemetsberger,et al.  (De-)stabilizing the digitized fashion market on Instagram–dynamics of visual performative assemblages , 2020, Consumption Markets & Culture.

[16]  Michele Zappavigna Searchable talk: the linguistic functions of hashtags , 2015 .

[17]  J. Rosenbaum Degrees of Freedom: Exploring Agency, Narratives, and Technological Affordances in the #TakeAKnee Controversy , 2019, Social Media + Society.

[18]  Alessandro Caliandro Digital Methods for Ethnography: Analytical Concepts for Ethnographers Exploring Social Media Environments , 2017 .