NEWS SOURCES AND HATE SPEECH IN THE 2020 ELECTION
Hate speech has become more visible on online social media platforms, particularly in the aftermath of political events such as the 2020 US elections. Numerous incidents in recent years have revealed that the offline consequences of online hate speech can be deadly. For example, considering the 2020 presidential election, different news agencies hosted online hate speech and harmful rhetoric,eventually leading to an attack on the Capitol.
This project explores overall usage of hate speech on news across the political spectrum during and after election. The question we aim to answer is: “Do the news sources have any profound impact on the violence by spreading hatred?” In addition, we want to discover whether hate speech increases on social media after the election or not? Lastly, we want to compare and contrast Fake News and True news websites and analyze Left-leaning and right-leaning websites from the perspective of hate speech. Through our analysis, we found that hate increased in news sources as major events took place. eg: election, capitol attack. We believe that this project will benefit Academic Researchers, Social Behavior Researchers, Social Sites, News Portals who want to block or flag links to fake news websites. In order to understand the social effect of hate speech during the 2020 US election, we ran short text topic modeling (SSTM) on left, right, and fake news media. The sentiment analysis of all the tweets in our data set suggested that we can categorize all tweets into three main topics: 2020 Presidential Election, handling coronavirus and rioting. We apply SSTM modeling once more on only hate tweets from left, right and junk news media. We can categorize the main themes of the hate tweets to racism, Black Lives Matter(BLM), nationalism, riots, police and topics related to the election. Overall, our results show that hate speech increased closer to the time of the Capitol attack.