Comparison: Widespread Worry and the Stock Market versus Sentiment Detection Engine for Internet Stock Message Boards

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Papers

  • Gilbert_et_al.,_ICWSM_2010 Gilbert, E. and Karahalios, K., Widespread worry and the stock market, 2010, In Proceedings of the international conference on weblogs and social media (ICWSM 10).

Method

Dataset Used

  • Chua et al in A Sentiment Detection Engine for Internet Stock Message Board used the data set HotCopper and collected posts between January-June 2004. This corpus is based in Australia.
  • Gilbert et al. in Widespread Worry and the Stock Market used two data sets: theLiveJournal blog data set and the S&P 500 data set. Both data sets are US based.

Overall, the papers used similar data sets and the primary difference was the geographic location of the blogs/discussion boards. Since these are financially focused forums, the geographic difference would indicate that the posts from the HotCopper is mostly from residents of Australia and the posts in the LifeJournal blog or S&P are primarily from the US. But this does not limit either corpus to those two regions as the bloggers can part-take in either web site.

Problem

Big Idea

Other

Additional Questions

1) How much time did you spend reading the (new, non-wikified) paper you summarized? ~2 hour

2) How much time did you spend reading the old wikified paper? ~1 hour

3) How much time did you spend reading the summary of the old paper? ~15 minutes

4) How much time did you spend reading background material? ~1 hour

5) Was there a study plan for the old paper? No

6) If so, did you read any of the items suggested by the study plan? and how much time did you spend with reading them? N/A

7) Other comments and feedback: It was an interesting assignment, but since we had to create two wiki pages, it was quite time consuming. It would be just as effective to have a short summary section in the comparison wiki page so that we can focus our attention to the comparison page. Otherwise, the exercise of comparing two studies in several categories (data set, methods, problem etc) was beneficial.

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