Smith, M. A., Rainie, L., & Shneiderman, B. (2014). Mapping twitter topic networks: From polarized crowds to community clusters. Pew Research Internet ….
Notes:
p.5: Social media is increasingly home to civil society, the place where knowledge sharing, public discussions, debates, and disputes are carried out. As the new public square, social media conversations are as important to document as any other large public gathering. Network maps of public social media discussions in services like Twitter can provide insights into the role social media plays in our society. These maps are like aerial photographs of a crowd, showing the rough size and composition of a population. These maps can be augmented with on the ground interviews with crowd participants, , collecting their words and interests . Insights from network analysis and visualization can complement surv vey or focus group research methods and can enhance sentiment analysis of the text of messages like tweets . — Highlighted Jan 30, 2016
p.5: Network measures of “centrality” can network, highlighting the people leading the conversation. The content these people create is often the most popular and widely repeated in these networks, reflecting the significant role these people play in social media discussions. — Highlighted Jan 30, 2016
p.14: Polarized Crowd social media networks feature at least two large dense groups connection or bridge between them . These networks are often focused on divisive topics especially likely to involve political content . — Highlighted Jan 30, 2016
p.22: the people who have no connections to Tight Crowd network conversations have few if any isolates – anyone else in the network. In network terms, isolates are people who use a hashtag or mention a topic, else who talked about the topic. but have not been observed to follow, reply to, or mention anyone Often, these are newcomers to the topic. — Highlighted Jan 30, 2016
p.29: People who tweet about brands and other public topics often form a network structure that is different from either the Tight Crowd or Polarized Crowd network communities. Brand Cluster networks often have very low density and many isolated participants. In a Brand Cluster network many people are likely to mention the brand without having any connection to other people who also mention the brand Advertised products, public events, and major n news events are likely to have this structure . — Highlighted Jan 30, 2016
p.36: a structure When evenly sized sub-groups, groups of people in Twitter form networks with several different from the Brand Clusters network emerges. Community Clusters are the defining quality of these networks: they feature a collection of medium sized groups, rather than a crowd of mostly . unconnected Twitter users — Highlighted Jan 30, 2016
p.42: The Broadcast Network structure is dominated by a hub and spoke structure, with the hub often being a a media outlet or prominent social media figure, surrounded by spokes of people who repeat the messages generated by the news organization or personality. — Highlighted Jan 30, 2016
p.47: Many large companies provide customer support via Twitter, maintaining a user account to listen to and reply to user complaints and issues. This account is often set up to reply to whoever tweets about the company, especially when service issues are cited. In this Twitter Support Network structure, the central account reaches out to many other accounts, but those other accounts are not usually linked to one another directly. It is a structure built on outflow more than on in bound conversation. — Highlighted Jan 30, 2016
p.54: Social media is used by millions of individuals who collectively generate an array of social forms from their interactions. Social media network maps can be useful in understanding the variety of social structures that emerge. Network maps c can reveal the structures of the crowd and highlight strategic locations or roles in these webs of connection. By mapping social media network spaces, , researchers and practitioners can learn about the most common and best uses for these communication services. — Highlighted Jan 30, 2016
See Also
- Del Vicario et al. (2016). The spreading of misinformation online
- Stewart (2015). Scholarship in abundance: influence, engagement, and attention in scholarly networks
- Cronin et al. (2015). Hierarchy is detrimental for human cooperation
- Imlawi et al. (2015). Student engagement in course-based social networks
- Gephi twitter community detection screencast