MS DEPARTMENT OF INFORMATION SYSTEM

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Browsing MS DEPARTMENT OF INFORMATION SYSTEM by Author "Abdul Rahim"

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    GOING DEEPER WITH RUMOR DETECTION
    (UMT, Lahore, 2021) Abdul Rahim
    The most trending topic of the year 2020 had been the Presidential elections of The United States of America, all the eyes were on this election because it defines the new rules and has deepening impacts for the whole world. In this event one of the most popular app twitter played an important role. Candidates used this social media platform to interact with their followers and to enhance election campaign. Mean-while, digital media was chocked with lot of false claims and rumors, which had great impact on sympathies and inclination of the voters. A whole nine-yard analysis of rumors via tweets across the world was taken up, focusing on Donald Trump. We used the dataset which contains the tweets having hashtag_donaldtrump keyword. And match this data with well-known factcheck websites and articles by using professional deep learning technique. We proposed the BERT model which is pretrained on larger corpus it is a type of transform learning which is good for training on small dataset and predict large data. To overcome the difficulty of labelling our dataset we scrap around 900 rumors and non-rumors data from different factcheck websites and then scrap around 450 tweets from official twitter account of Donald Trump and merge it into one file after collecting this data we annotate it manually. We train our BERT model on this dataset and predict around one million tweets. The results adequately provide answers to several major rumors and the related stuff as how rumors influence and how the typical manipulation undergoes? Which countries are the main source of rumors, which US state followers spread the rumors most, and which twitter application was used the most for posting rumor tweets? The insights of this research helped us understand as how rumors were generated and how did they effect the mindsets in the recent elections in US.