Descriptive analysis of suicide ideation on Twitter

The start of the online social networks have caused an spike in interactions between people. While this has a positive impact in society, it can also spread the ideations of suicide leading to the contagion effect.We used live twitter data for
our database along with previously labelled twitter data and draw conclusions about the data to gain an insight on the possible behavior of users who are going through suicidal thoughts. We observed that people who are popular and
very active on social media are likely to be depressed. We visualized a word cloud of the most popular word addressed by said depressed people. We also performed K means clustering on the tweets and obtained 6 clusters. We believe our
work has helped gain some insight on suicide ideation on twitter.