Keywords based temporal sentiment analysis

Free texts such as comments by customers or readers, contain not only the sentiments of the topic being talked about but also temporal trends of the sentiments. Sentiment detection automatically estimates the polarity of the comments as positive, negative or sometimes neutral. On the other hand, a temporal sentiment analysis in an investigation of the sentiment pattern within a given time period. We propose a method for investigating the temporal patterns using keywords in the comments. We managed to relate a few major events that occurred during the time period of investigation (19 November - 20 December 2014) using sentiment classification techniques and keyword clustering. The results of this work show how temporal sediment analysis could be used to establish the changes in opinions from the pubic relating to issues-events in a historically important election campaign in a developing country. The results show interesting information on the change of opinions during this election campaign impossible to learn by other means.