Difference between revisions of "Class Meeting for 10-802 01/18/2011"

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** Any special skills you have, research interests that you have, related projects you have been or might be working on, etc.
 
** Any special skills you have, research interests that you have, related projects you have been or might be working on, etc.
  
=== Papers you might present ===
+
=== Papers you might review ===
  
 
The Pang and Lee survey has a wealth of references.  Some I recommend are:
 
The Pang and Lee survey has a wealth of references.  Some I recommend are:
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* Yang, K., N. Yu, A. Valerio, H. Zhang, and W. Ke. 2007. Fusion approach to finding opinions in Blogosphere. In Proc Intern Conf on Weblogs and Social Media, Boulder, Colorado.
 
* Yang, K., N. Yu, A. Valerio, H. Zhang, and W. Ke. 2007. Fusion approach to finding opinions in Blogosphere. In Proc Intern Conf on Weblogs and Social Media, Boulder, Colorado.
  
Some interesting recent papers include:
+
Some adduitional interesting recent papers include:
  
 
* Fagerlund, M., L. Eldén, M. Merkel, and L. Ahrenberg. 2010. Computing Word Senses by Semantic Mirroring and Spectral Graph Partitioning. ACL 2010: 103.
 
* Fagerlund, M., L. Eldén, M. Merkel, and L. Ahrenberg. 2010. Computing Word Senses by Semantic Mirroring and Spectral Graph Partitioning. ACL 2010: 103.

Latest revision as of 10:44, 6 September 2012

This is one of the class meetings on the schedule for the course Social Media Analysis 10-802 in Spring 2011.

Overview

Readings

  • Pang & Lee survey, remainder. The lecture won't cover quite the same material, but I highly recommend reading this anyway.

Assignment

  • Go to http://malt.ml.cmu.edu/mw and create an account for yourself (use andrew id)
  • Go to your user page and add
    • Your real name & a link to your home page
    • Who you are and what you hope to get out of the class (Let me know if you’re just auditing)
    • Any special skills you have, research interests that you have, related projects you have been or might be working on, etc.

Papers you might review

The Pang and Lee survey has a wealth of references. Some I recommend are:

  • Andreevskaia, A., S. Bergler, and M. Urseanu. 2009. All Blogs Are Not Made Equal. In Proc Intern Conf on Weblogs and Social Media, San Jose.
  • Danescu-Niculescu-Mizil, C., G. Kossinets, J. Kleinberg, and L. Lee. 2009. How Opinions are Received by Online Communities: A Case Study on Amazon. com Helpfulness Votes. WWW 2009.
  • Esuli, A., and F. Sebastiani. 2006. SentiWordNet: A publicly available lexical resource for opinion mining. In Proceedings of LREC, 6: Vol. 6.
  • Kessler, J. S, and N. Nicolov. 2009. Targeting Sentiment Expressions through Supervised Ranking of Linguistic Configurations. In Proceedings of the 3rd Intl. Conference on Weblogs and Social Media (ICWSM 2009), San Jose.
  • Takamura, H., T. Inui, and M. Okumura. 2005. Extracting semantic orientations of words using spin model. In Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, 140.
  • Yang, K., N. Yu, A. Valerio, H. Zhang, and W. Ke. 2007. Fusion approach to finding opinions in Blogosphere. In Proc Intern Conf on Weblogs and Social Media, Boulder, Colorado.

Some adduitional interesting recent papers include:

  • Fagerlund, M., L. Eldén, M. Merkel, and L. Ahrenberg. 2010. Computing Word Senses by Semantic Mirroring and Spectral Graph Partitioning. ACL 2010: 103.
  • Hassan, A., and D. Radev. 2010. Identifying text polarity using random walks. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, 395–403.
  • Passos, A., J. Wainer, and A. Haghighi. n.d. What do you know? A topic-model approach to authority identification.
  • Tsur, O., D. Davidov, and A. Rappoport. 2010. ICWSM-A Great Catchy Name: Semi-Supervised Recognition of Sarcastic Sentences in Online Product Reviews. Proceeding of ICWSM.
  • Zhao, Xin, Jing Jiang, Hongfei Yan, and Xiaoming Li. 2010. Jointly Modeling Aspects and Opinions with a MaxEnt-LDA Hybrid. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, 56–65. Cambridge, MA: Association for Computational Linguistics, October. http://www.aclweb.org/anthology/D10-1006.