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[[1]| My webpage]

Hi There. My name is Subhodeep Moitra.

I am a Masters student in the Language Technologies Institute, School of Computer Science at Carnegie Mellon University. I am working with Prof. Judith Klein Seetharaman and Prof. Christopher James Langmead on problems in Computational Biology.

My primary areas of interest are Computational Biology, Machine Learning and Statistics.

I was born in the city of New Delhi and since then have stayed in a number of places for varying lengths of time. I like learning new languages and so far have made an attempt in Bengali, Hindi, Tamil, English, French, German and Spanish. I love running. I will be doing the Pittsburgh Marathon and I will be running for AID, a charitable cause.

Many of the problems in Biology can be cast in terms of networks of interacting entities. Very often these have patterns similar to social network behavior. At some level, social behavior is a very very high level of abstraction from the molecular entities inside our body. I hope to gain some insights into the prevalent methods in social media and how they might be applied to biological problems.


Wiki pages Created


Project Proposal

Finding bias-groups in discussions on blogs

Team Members

Subhodeep Moitra ( Srivastava (

Data Set

Yano and Smith dataset of blogs and comments from 40 blog-sites focused on American politics [2]

Goal of the Project

We aim at modeling and estimating the bias groups among the users who make comments on blogs. For any blog, the users making comments either agree or disagree with the opinions of the author or of other users making comments. Also, these agreements and disagreements could be on various sub-topics discussed within a single blog. We aim at estimating which users are agreeing or disagreeing on what sub-topics of a given blog. We have gone through few papers which tackle different aspects of this problem separately. Hu et. al. [1] did extraction based summarization of sentences from blog-posts based on the content of the comments. Such an attempt is useful for us, so that we can relate the discussions in the comments with the sub-topics in the blog-posts. Another interesting work by Mishne and Glance [2] aims at detecting disputes in comments to web-blogs, which again relates to what we attempt to do. Another paper by Schuth et. al. [3] aims at finding the comments which relate to one thread of discussion. This is particularly useful in cases where the users cannot reply to other users’ comments explicitly. The techniques used in this paper could be useful in our case, to find out the likely discussion thread among all the posts on a certain blog.


1] Hu M., Sun A., Lim E., “Comments-Oriented Blog Summarization by Sentence Extraction”, 16th ACM Conference on Information and Knowledge Management, 2007

[2] Mishne G., Glance N., “Leave a Reply: An Analysis of Weblog Comments”, Third Annual Workshop on the Web-logging Ecosystem, 2006 [3] Schuth A., Marx M., Rijke M., “Extracting the discussion structure in comments on news-articles”, Proceedings of the 9th Annual ACM Workshop on Web-Information and Data Management, 2007