Comparison: O'Connor et al. ICWSM 2010 & Widespread Worry and Stock Market

Papers

Brendan O’Connor, Ramnath Balasubramanyan, Bryan R. Routledge, and Noah A. Smith. 2010a. From tweets to polls: Linking text sentiment to public opinion time series. In Proc. of ICWSM. OConnor et. al., ICWSM 2010

Method

The two papers used different methodologies. The O'Conner et al. paper studied sentiment analysis of Twitter data by using a sentiment lexicon to mark positive or negative tweets, whereas the Gilbert et al. paper used supervised learning classifiers to automatically identify anxious LiveJournal blog posts. Furthermore, Gilbert et al. analyzed the usefulness of time series data from their Anxiety index in forecasting S&P 500 stock market data using Granger causality, whereas O'Connor et al. simply studied the smoothed correlation between public opinion polls and their aggregated Twitter sentiment.

Dataset Used

• Gilbert et al. used two data sets: LiveJournal blog dataset and the S&P 500 dataset.
• O'Connor et al. uses a dataset consisting of roughly 1 billion Twitter posts collected between 2008-2009.

Additional Questions

How much time did you spend reading the (new, non-wikified) paper you summarized? 3 hours

How much time did you spend reading the old wikified paper? 2 hours

How much time did you spend reading the summary of the old paper? 10 minutes

How much time did you spend reading background materiel? Half an hour

Was there a study plan for the old paper? Yes

If so, did you read any of the items suggested by the study plan? and how much time did you spend with reading them? No.

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