The project focuses on minimizing the spread of a rumour in a twitter network by identifying most active or influential users.
Twitter has become a very influential social media platform. Twitter statements from public figures are nowadays becoming front page news. Hence it is a social responsibility of one that the information going on twitter must be genuine. To measure the activity rate, we have extracted a wide number of factors like likes, comments, retweets, timestamp, etc. The dataset selected to perform this analysis was extracted from twitter with the help of searchtweets and tweepy packages in python.
- Extracting the dataset from Twitter.
- Extracting information of user whose tweets have been extracted.
- Recognizing authentic users.
- Checking whether they follow each other or not.
- Creating a csv file of the users along with their followers count.
- Extracting the user ids of followers.
- Plotting a graph of followers and following.
- Finding out most active user.
- Using DAVA algorithm to find the nodes on whose removal the spread of rumour can be minimized.
-@bhavyamendiratta - Bhavya Mendiratta
-@harshitabajaj - Harshita Bajaj
-@youngbuck09 - Dhanesh Chaudhary
-@jindalraghav98 - Raghav Jindal