NSF EAGER: Data-Driven Framework for Analyzing User Interactions in Social Media
With hundreds of millions of users worldwide, social networks provide incredible opportunities for social
connection, learning, political and social change, and individual entertainment and enhancement in a wide
variety of forms. In light of these notable outcomes, understanding information diﬀusion over online so-
cial networks is a critical research goal. Because many social interactions currently take place in online
networks, social scientists have access to unprecedented amounts of information about social interaction.
Prior to the advent of such online networks, these investigations required resource-intensive activities such
as random trials, surveys, and manual data collection to gather even small data sets. Now, massive amounts
of information about social networks and social interactions are recorded. This wealth of data can allow
social scientists to study social interactions on a scale and at a level of detail that has never before been
possible. Research in social network analysis, however, requires inter-disciplinary collaboration. This pro ject
is an integrated research approach for analyzing user interactions in online social networks that combines
expertise in three key areas: (1) Collection, Querying, and analysis of massive datasets (2) Modeling and
analysis of complex networks (3) Analysis of social media and social interactions in the contemporary media
environment. The overarching goals are to generate a greater understanding of social interactions in online
networks through data analysis, to evaluate and validate existing models of social processes, and ultimately
to create a shared data repository and a collection of evaluation metrics that can be used broadly by other
research investigations in social networks.
The work proposed in this pro ject is high-risk since social networks and media are still evolving and
our understanding of such information ecosystem is still nascent. However, at the same time, this work
comes with a high-reward since a successful execution of this pro ject will essentially result in revolutionary
approaches for testing and validating human behaviors and interactions in a society at diﬀerent scales.
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