Abstract

http://ssrn.com/abstract=276189
 
 

Citations (46)



 
 

Footnotes (16)



 


 



Yahoo! for Amazon: Sentiment Parsing from Small Talk on the Web


Sanjiv Ranjan Das


Santa Clara University - Leavey School of Business

Mike Y. Chen


University of California, Berkeley

August 5, 2001

EFA 2001 Barcelona Meetings

Abstract:     
The internet has made it feasible to tap a continuous stream of public sentiment from the world wide web, quite literally permitting one to "feel the pulse" of any issue under consideration. We present a methodology for real time sentiment extraction in the domain of finance. With the advent of the web, there has been a sharp increase in the influence of individuals on the stock market via web-based trading and the posting of sentiment to stock message boards. While it is important
to capture this "sentiment" of small investors, as yet, no index of sentiment has been compiled. This paper comprises (a) a technology for extracting small investor sentiment from web sources to create an index, and (b) illustrative applications of the methodology. We make use of computerized natural language and statistical algorithms for the automated classification of messages posted on the web. We design a suite of classification algorithms, each of different theoretical content, with a view to characterizing the sentiment of any single posting to a message board. The use of multiple methods allows imposition of voting rules in the classification process. It also enables elimination of "fuzzy" messages which are better off uninterpreted. A majority rule across algorithms vastly improves classification accuracy, but also leads to a natural increase in the number of messages classified as "fuzzy". The classifier achieves an accuracy of 62% (versus a random classification accuracy of 33%), and compares favorably against human agreement on message classification, which was 72%. The technology is computationally efficient, allowing the access and interpretations of thousands of messages within minutes. Our illustrative applications show evidence of a strong link between market movements and sentiment. Based on approximately 25,000 messages for the last quarter of 2000, we found evidence that sentiment is based on stock movements.

Number of Pages in PDF File: 45

working papers series


Download This Paper

Date posted: July 11, 2001  

Suggested Citation

Das, Sanjiv Ranjan and Chen, Mike Y., Yahoo! for Amazon: Sentiment Parsing from Small Talk on the Web (August 5, 2001). EFA 2001 Barcelona Meetings. Available at SSRN: http://ssrn.com/abstract=276189 or http://dx.doi.org/10.2139/ssrn.276189

Contact Information

Sanjiv Ranjan Das (Contact Author)
Santa Clara University - Leavey School of Business ( email )
Department of Finance
321E Lucas Hall
Santa Clara, CA 95053
United States
HOME PAGE: http://algo.scu.edu/~sanjivdas/
Mike Y. Chen
University of California, Berkeley ( email )
Computer Science Division
Berkeley, CA 94720
United States
Feedback to SSRN


Paper statistics
Abstract Views: 20,785
Downloads: 1,236
Download Rank: 7,952
Citations:  46
Footnotes:  16

© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollo8 in 0.313 seconds