Difference between revisions of "User:Manajs"

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Name: Manaj Srivastava
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<p align="left">[[File:ms.jpg]]</p>
  
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Home-page: http://www.cs.cmu.edu/~manajs/
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<b>Manaj Srivastava</b>
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http://www.cs.cmu.edu/~manajs/
  
 
Who I am and why I am here:
 
Who I am and why I am here:
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I am a second year Masters student in the LTI. I have taken this course because the syllabus matter aligns pretty well with my current research on Information Extraction.
 
I am a second year Masters student in the LTI. I have taken this course because the syllabus matter aligns pretty well with my current research on Information Extraction.
  
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<Details from "Analysis of Social Media" course taken in Spring, 2011 follows...>
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Click [[Information Extraction to Predict Decisions|here]] to go to the project page.
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[[Analysis of Social Media Spring, 2011|Link]] to my wiki page for the "Analysis of Social Media" course taken in Spring, 2011.
  
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Intention behind taking the course:
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Interest in social media, which is a rapidly growing phenomenon on web. Along with other things, i was particularly interested in modeling and analysis of the discussion between people in online forums, or as comments to blogs or news-stories. Such comments are pretty interesting in terms of their length and the kind of information they carry--while some are pretty small and loosely written, others are long and well-crafted ones. Want to do a project on similar lines analyzing this domain of social interaction.
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'''Wiki Writeups'''
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Research Interests:
 
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Language Technologies, Semantic Analysis, Discourse Analysis and Text modeling.
 
  
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---
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[[Semantic Role Labeling with CRF|Cohn and Blunsom: Semantic Role Labeling with Tree Conditional Random Fields - Paper (due 10/1)]]
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==Wiki Pages Created==
 
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====[[Blog summarization: CIKM 2007]]====
 
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====[[Identifying influential bloggers: WSDM 2008]]====
 
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====[[Analyzing and Predicting Youtube Comments Rating: WWW2010]]====
 
  
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== Project Proposal ==
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[[Semantic Role Labeling as Sequential Tagging|Marques et. al.: Semantic Role Labeling as Sequential Tagging - Paper (due 10/1)]]
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Finding bias-groups in discussions on blogs
 
  
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== Team Members ==
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[[Learning Domain-Specific Information Extraction Patterns from the Web|Patwardhan and Riloff: Learning Domain-Specific Information Extraction Patterns from the Web - Paper (due 10/1)]]
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Subhodeep Moitra (smoitra@cs.cmu.edu)
 
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Srivastava (manajs@cs.cmu.edu)
 
  
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== Data Set ==
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[[Semantic Affinity|Semantic Affinity - Method (due 10/1)]]
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Yano and Smith dataset of blogs and comments from 40 blog-sites focused on American politics [http://www.ark.cs.cmu.edu/blog-data/]
 
  
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== Goal of the Project ==
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[[Unsupervised Modeling of Dialog Acts in Asynchronous Conversation | Joty et. al.: Unsupervised Modeling of Dialog Acts in Asynchronous Conversation - Paper (due 11/2)]]
  
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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.
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[[Modeling of Stylistic Variation in Social Media with Stretchy Patterns | Gianfortoni et. al.: Modeling of Stylistic Variation in Social Media with Stretchy Patterns - Paper (due 11/2)]]
  
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== References ==
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[[Joint Inference in Information Extraction | Poon and Domingos: Joint Inference in Information Extraction - Paper (due 12/1)]]
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1] Hu M., Sun A., Lim E., “Comments-Oriented Blog Summarization by Sentence
 
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Extraction”, 16th ACM Conference on Information and Knowledge Management, 2007
 
  
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[2] Mishne G., Glance N., “Leave a Reply: An Analysis of Weblog Comments”, Third Annual Workshop on the Web-logging Ecosystem, 2006
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[[Automatic Detection and Classification of Social Events | Agarwal and Rambow: Automatic Detection and Classification of Social Events  - Paper (due 12/1)]]
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[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
 

Latest revision as of 06:34, 7 December 2011

Ms.jpg

Manaj Srivastava

http://www.cs.cmu.edu/~manajs/

Who I am and why I am here:

I am a second year Masters student in the LTI. I have taken this course because the syllabus matter aligns pretty well with my current research on Information Extraction.

Click here to go to the project page.

Link to my wiki page for the "Analysis of Social Media" course taken in Spring, 2011.

Wiki Writeups

Cohn and Blunsom: Semantic Role Labeling with Tree Conditional Random Fields - Paper (due 10/1)

Marques et. al.: Semantic Role Labeling as Sequential Tagging - Paper (due 10/1)

Patwardhan and Riloff: Learning Domain-Specific Information Extraction Patterns from the Web - Paper (due 10/1)

Semantic Affinity - Method (due 10/1)

Joty et. al.: Unsupervised Modeling of Dialog Acts in Asynchronous Conversation - Paper (due 11/2)

Gianfortoni et. al.: Modeling of Stylistic Variation in Social Media with Stretchy Patterns - Paper (due 11/2)

Poon and Domingos: Joint Inference in Information Extraction - Paper (due 12/1)

Agarwal and Rambow: Automatic Detection and Classification of Social Events - Paper (due 12/1)

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