Sentiment140 is a tool that allows you to evaluate a written text in order to determine if the writer has a positive or negative opinion about a specific topic. Facing 2015 Argentinian presidential election we are going to evaluate the public image of the most important candidates: Sergio Massa, Mauricio Macri and Daniel Scioli. For this purpose we are going to use the python library called Tweepy to collect thousands of tweets in which they are mentioned.
What is sentiment analysis?
Sentiment analysis aims to determine the attitude of a speaker or writer with respect to some topic or the overall contextual polarity of the document. The attitude may be his or her judgment or evaluation, affective state or the intended communication.
Written text can be broadly categorized into two types: facts and opinions.
- Opinions carry people’s sentiments and feelings. These kind of texts can be classified in positive or negative. For example if we get the following text: “I would like to see Macri as president” we can suppose that the speaker has a positive opinion about the candidate. In the same way, if we get the text: “I wouldn’t like to see Macri as president” we can suppose that the speaker has a negative impression about him.
- A fact can be for example: “Today Macri visited three neighborhoods“. We should ignore these kind of texts because we can’t determine if the writer has a positive or a negative opinion about the politician.