Monthly Archives: May 2010

Hand Washing Diminishes Cognitive Dissonance Effect

by Yunkyu Sohn

What we do when we confront multiple contradicting ideas? The theory of cognitive dissonance asserts that people tend to manipulate their preference, attitude or opinion to evade such uncomfortable situations. Psychologists developed a standard experimental setup to assess the presence of such tendency. In this setup, the experimenter asks subjects to rank N objects according to their preference and offers n<N objects to them. After the transaction was made the subjects are asked to re-rank N products. Many experimental studies have found that the subjects are likely to alter their preference ordering. That is, they tend to rank those n objects higher afterward. Two fMRI studies (Sharot, Martino and Dolan 2009; Veen et al. 2009) revealed that dorsal anterior cingulate cortex anterior insula, caudate nucleus and amygdala underly certain behavior.

In a recent Brevia published in Science, Lee and Schwarz report that ordinary hand washing task removes the consequential preference shift caused by cognitive dissonance. This study extends the findings of previous studies which examined the role of physical cleansing on compensatory behavior and moral judgement, and demonstrates that it also has implications on people’s preference consistency. The link found in these works may elucidate result of voters’ physical and physiological activities on their political attitudes and decisions (see Mullainathan and Washington on cognitive dissonance in voting).

Does moral action depend on reasoning?

An interesting set of discussions by leading scholars in moral psychology:

Congressional Speech Corpus (including references to other members of Congress)

By Jason J. Jones

I ran across this corpus of Congressional speech that may be useful to some in the group.  Here is a brief description:

This data includes speeches as individual documents, together with:

  • automatically-derived labels for whether the speaker supported or opposed the legislation discussed in the debate the speech appears in, allowing for experiments with this kind of sentiment analysis
  • indications of which “debate” each speech comes from, allowing for consideration of conversational structure
  • indications of by-name references between speakers, and the scores that our agreement/disagreement classifier(s) automatically assigned to such references, allowing for experiments on agreement classification if one assigns “true” labels from the support/oppose labels assigned to the pair of speakers in question
  • the edge weights and other information we derived to create the graphs we used for our experiments upon this data, facilitating implementation of alternative graph-based methods upon the graphs we constructed

The third bullet seems like it would be of particular interest.

In my data mining class we are not using this corpus, unfortunately.  But, if you want to know which words most likely indicate an unfavorable movie review, I should have a classifier that will tell you by next week.