Big Data & Data Analytics: Assignment week 11 "Text Mining Analysis" : Tweets #ShameOnYouSyedSaddiq

Big Data & Data Analytics: Assignment week 11 "Text Mining Analysis" : Tweets #ShameOnYouSyedSaddiq

Well, it seems like this one hashtag successfully got the first rank in the trending topic of a social media, Twitter. This time, I tried to find out what words and how many words came out on the tweets containing the hashtag. I did a text mining analysis using the Orange application with the classification method and here are the results:

Pic 1: Display

This picture shows the display of how I use the Orange. The attributes are:

- From text mining: Twitter, Corpus Viewer, Preprocess Text, Topic Modelling, Word Cloud, Sentiment Analysis, and Tweet Profiler.

- From Visualize: Box Plot

Pic 2: result of Corpus Modelling

From the picture above (Pic 2), we can see I took 100 tweets from Twitter that contains with the hashtag of #ShameOnYouSyedSyaddiq .

Pic 3: result of Topic Modelling

 Based on the picture that I put (Pic 3), with the number of topics are 10. The words with the green color mean the stronger words than the red words.

Pic 4: result of Word Cloud

 With 100 tweets that I took as the sample, it has 100 tweets with 770 words. And from that picture, we can see the weighting of the words. The word that has the highest weight is "shameonyousyedsaddiq" with the weight is 103, followed by "syedsaddiq" with the weight is 42, and for the third top word is "maaf" with the weight is 26.

Pic 5: result of Box Plot

As we can see that the result of Box Plot shows how someone's sentiments when writing something on Twitter. There are five sentiments (or emotion) that appear because of the tweets that contain of  the hashtag. The sentiments are anger, disgust, fear, joy, and surprise. Every sentiment has the username that has their own percentage of how big their sentiments. But in this picture, I'm sorry that I can't show you the number of percentage because it is not appear in mine :( .

So the conclusion is that the tweet containing the hashtag #ShameOnYouSyedSaddiq analyzed using the Orange app is that using 100 tweets taken with 770 words can generate five kinds of sentiments namely anger, disgust, fear, joy, and surprise.