This experiment analyzes “tweets” gathered from Twitter and determines whether the positive or negative emotions conveyed in the contents of a massive collection of these tweets correlate with the percentage change in indexes of Standard & Poor's 500, the Dow Jones Industrial Average, and the NASDAQ stock markets. This experiment uses an algorithm that parses a random sample of live tweets and calculates their sentiment value, which is an indicator of whether a tweet is either negative or positive in its emotional content. The daily average sentiment value is then compared to the percent change in the stock exchanges.
| Identifer | oai:union.ndltd.org:CLAREMONT/oai:scholarship.claremont.edu:cmc_theses-2106 |
| Date | 01 January 2014 |
| Creators | Langdon, Stephen |
| Publisher | Scholarship @ Claremont |
| Source Sets | Claremont Colleges |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | CMC Senior Theses |
| Rights | © 2014 Stephen Langdon, http://creativecommons.org/licenses/by-nd/3.0/ |
Page generated in 0.0049 seconds