A Clustering Analysis of Tweet Length and its Relation to Sentiment
arXiv:1406.3287v32.03 citationsHas Code
Originality Synthesis-oriented
AI Analysis
This work addresses sentiment analysis for Twitter users, but it appears incremental as it builds on existing dictionaries and clustering techniques.
The paper tackled sentiment analysis on Twitter by developing a method to create sentiment score dictionaries from seed words and analyzing how sentiment scores cluster with tweet length, but no concrete numerical results were reported.
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.