Goal

• Extract 50 tweets under topic “Bentley Student ”

• Analyzing demographics of users twitter about the topic

• Social network about users

• Identify the influential user

• Analyzing content about tweet

Packages

Extract Data : getoldtweet3, tweepy

General description of the data : Pandas, Numpy, Matplotlib, Seaborn

Social network Analysis: Networkx

Text Analysis: nltk, sklearn, textblob

General description of the data

Time : From plot, most people tweet on 4.24. On average, 5 tweets post are about bentley student every day.

Retweet and Like: Since it’s recently tweet, all of tweets don’t have retweet. And most people get 0 likes. But still some post get five or six like.

Social Network Analysis

Soical Network Graph

Sentiment Analysis

Most tweet are negative and neutral. Most tweet are objective topic

Negative tweet Example

Conclusion and Limitation

Conclusion

• People like to follow politic figure, News account and public department.

• The influential people in the network are Barack Obama : )

• People go tweet about bentley university mostly about introducing bentley, make advertising about student event and ask for help for student affairs.

Limitation

• The polarity and subject class cutoff may need improved.

• Need other packages to improve the sentiment analysis result.

• Need more time to extract data

Code

Twitter Data Analysis