How influencers help spread information across Twitter

Motivation

Have you ever gotten those pesky posts that pop up over and over again on Twitter that get you thinking, “How many people even look at this?”. Or maybe you’re sharing a cute puppy photo you took and wondering “How can I get more people to see my posts?”

Well, you’re not alone. Analyzing how information spreads in social networks like Twitter is an important and relevant problem that reveals how online communities dictate the status quo like which topics are trending or which news story receives greater exposure. The answer to many of these questions lies in the fact that users with large networks such as influencers, organizations or news sites often dictate how information is shared on Twitter.

Analysis

The sports industry, specifically cycling, sets a productive environment to investigate these issues further as cycling teams, athletes and organizations often promote races and events on Twitter, leading to networks of interaction and information sharing. To investigate information spread within Twitter’s online social network, sports researcher Marion Hambrick analyzed the social networks produced from Twitter promotions of two separate events; a local and national cycling race in the United States. Hambrick’s study noted “quick network expansion and short information life spans on Twitter” in which event posts received increased engagement close to when promotion material was first posted with a steep decrease in retweeting and network expansion after approximately 4 days.

Furthermore, he found that the race organizers’ networks grew when followers with large networks joined early on. A similar concept called the core-periphery network structure was encountered in lecture which describes how nodes in the network’s core are easier to find than nodes in the periphery.

In the study, users in the periphery with a low follower count were still able to find event information from users in the core with a large network who retweeted event posts and acted as information hubs to increase information spread greatly. By adopting a network science approach to analyzing social networks, we can better interpret how information circulates in a matter of days through followers with large networks to reach isolated sub-networks as in Hambrick’s study .

In the above images, note the edges between nodes on the perimeter denoting sub-communites forming, and the edges connecting to the core from isolated nodes (particularly in the local race’s network).

Another result from the study was that users within the network also became involved in smaller sub-communities with similar interests. We explored a similar idea in lecture with Granovetter’s theory suggesting that networks are composed of tightly connected sets of nodes. Applying this idea, we see that development of sub-communities within the study’s network result from existing relationships, such as users with existing connections over a separate shared interest creating relationships with new users who are also attending the cycling race. Think about the last time you connected with someone at an event. If they had a large network, they could be a great resource to find out about relevant events, other similar communities, or even others who share the same interests!

Conclusion

So the next time a cute puppy comes across your feed, take a minute to consider the path the post has taken to reach your feed, and how users with large networks like influencers have shortened the path length to deliver you those fluffy corgis!

Reference

Hambrick, Marion E. “Six Degrees of Information: Using Social Network Analysis to Explore the Spread of Information Within Sport Social Networks”. International Journal of Sport Communication 5.1 (2012): 16-34. < https://doi-org.myaccess.library.utoronto.ca/10.1123/ijsc.5.1.16>. Web. 21 Oct. 2022.