Widespread Worry and the Stock Market

This a Paper for Social Media Analysis 10-802 in Fall 2012.

Citation

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),

Online version

Widespread worry and the stock market

Summary

This paper attempts to find correlations between LiveJournal blog post sentiment and S&P 500 stock market changes, using opinion mining. The authors used supervised learning techniques to classify posts in a binary fashion into sets of *anxiety posts* and *not anxious posts*. The classifiers used had low recall (28% and 32%), but high precision, with false positive rates of 3% and 6%. Thus, the classifiers were conservative in assigning posts to the anxious class.

Using the classifier labeled posts, an **Anxiety index** was created by taking the fraction of of anxious posts per day and taking the difference of the logarithm of such values for two consecutive days. This anxiety time series was compared to the S&P 500 time series, where for the S&P data, the difference of consecutive log-returns was used, namely $M_{t}=\log(R_{t+1})-\log(R_{t})$.

To evaluate if there existed correlation between the anxiety index and the S&P 500 data, the authors turned to Granger Causality, which is a statistical hypothesis test for determining whether one time series is useful for forecasting another.

Results

The authors found, in one instance, a significant

Related papers

• Esuli and Sebastiani EACL 2006 is the author's prior work that led to the topic of the current paper.
• Andreevskaia and Bergler EACL 2006 discusses sentiment tag extraction from WordNet glosses.
• Hatzivassiloglou and McKeown ACL 1997 describes early work in using sentiment word lists to classify text sentiment.
• Yu and Hatzivassiloglou EMNLP 2003 investigates the problem of identifying objective and sentimental sentences and determining their polarity.

Study plan

Some concepts which made aid in understanding this paper

• Term Frequency, Inverse Document Frequency (tf * idf)
  • A tutorial slideshow discussing the particular method the authors used to vectorize and weight synset glosses.
• WordNet
  • A description of the WordNet lexical resource.
• WordNet Home