CS Postdoc Profiles

Research Profile

My research interests lie at the intersection of automatic social content analysis and computational social science. My interest is in finding innovative and robust computational ways of coding and analyzing behavioral data on social media and answering questions about the underlying social processes.

In my most recent work I have focused on making sense of social (textual) data, drawing from the fields of statistical Natural Language Processing (NLP), Machine Learning, Social Web and the Semantic Web to tackle a diverse set of information extraction problems and to power Social Intelligence applications. My research has focused on answering three broad questions in the analysis of Social Media content:
- Characterizing what people are talking about What are the named entities and topics that people are making references to? How are cultures interpreting any situation in local contexts and supporting them in their variable observations on a social medium?
- Characterizing how they express themselves What do word usages tell us about an active population or about individual allegiances or non-conformity to group practices?
- Characterizing why they scribe What are the diverse intentions that produce the diverse content on social media? Can we understand why we share by looking at what we predominantly do with the medium? What emotions are people conveying about a person, event or incident?

Several results of my work have been absorbed into two deployed social intelligence Web applications. First, the BBC SoundIndex (www.almaden.ibm.com/cs/projects/iis/sound/), that measures the pulse of a music populace by tapping into content from online music communities for the end goals of popularity mining. The second web application, Twitris (http://twitris.knoesis.org) aggregates user perceptions behind real-time events using data from Twitter.

My future interests are in grounding social data analysis in Communication theory, understanding a social process in the context of people, content and network connections –“who (people) said what (content) to whom (network structures) in what channel with what effect”; and in interpreting results of the computational analyses using theories of information/social science.

More information can be found on my webpage http://knoesis.wright.edu/researchers/meena/ and CV http://knoesis.wright.edu/researchers/meena/homepage/resume.pdf

Contact Information

E-Mail: EMAIL OBFUSCATED

Categories Posted To:

Information Systems / Information Science, Social Computing / Social Informatics