Presentation to accompany research paper. Research abstract: Sentiment analysis of Twitter data is performed. The researcher has made the following contributions via this paper: (1) an innovative method for deriving sentiment score dictionaries using an existing sentiment dictionary as seed words is explored, and (2) an analysis of clustered tweet sentiment scores based on tweet length is performed.

1. A CLUSTERING ANALYSIS OF
TWEET LENGTH AND ITS
RELATION TO SENTIMENT

2. Research Project
Matthew Mayo
School of Computer Science
Columbus State University
Columbus, GA 31907
CPSC 6185 Intelligent Agents
Dr. Rania Hodhod

3. Twitter
• Popular microblogging web service
• 140 character per message (tweet) limit
• Started in 2006, over 645 million users today*
• 58 million tweets per day*
• 9,000 tweets per minute*
* Source: www.statisticbrain.com/twitter-statistics

4. Sentiment Analysis
• Identifying, extracting & processing subjective
information from source material
• Subjective information includes attitudes, emotions
& opinions
• Appropriate for binary classification (positive vs.
negative, good vs. bad, etc.)
• Useful for movie reviews, political election opinions,
etc.

5. Project Aim
Interested in exploring the relationship between:
• Length of tweet (number of characters)
AND
• Sentiment score of tweet

6. Problem Description
The research project tasks:
1. Capture Twitter data
2. Build custom sentiment dictionary
3. Process tweets
4. Create dataset
5. Cluster tweet data