Text Mining (Sentiment Analysis, Topic Modelling, Word Cloud)

I would like to do Text Mining Analysis by using Orange 3 to know the Sentiment Analysis, Topic Modelling and Word Cloud.

The picture above is the layout of Orange 3 when we want to do the analysis, I was connected to Twitter to get the API's key and API's key secret. The topic that I choose is discussed about #Seungri Bigbang that now is involved in the case of prostitution, and I took 100 samples of tweets.

Sentiment Analysis


We can see that there are 4 sentiments, which are fear, joy, sadness, and surprise. Related to the topic, there are so many people or Seungri's fans got surprised about his case that he involved in prostitution. Then, we can see that sadness and fear by his fans comes up because it is happens to Seungri Bigbang. Sentiment Analysis is used to explain how sentiment the user of Twitter about the topics, it also the emotion that related with an individual.

Topic Modelling


In topic modelling, we can see that there are 10 keywords that used by the user of Twitter. It mentioning the keywords that related to the topic.

Word Cloud


Word Cloud is about the words that users always mention. As we can see "Seungri" is the most frequently mentioned word, and there were 962 words collected from 100 samples.

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