The last elections have shown that politicians are getting away with posting hate speech and false information on their social media feeds.

What it does

We want to provide a tool that allows to analyse politicians social media feeds in regard to hate, information credibility and sentiment analysis. Moreover, it's not only a search page, but also a chrome plugin to directly extract and check content from websites.

How we built it

We have used several tools:

  • main language is python, pandas and nltk for sentiment analysis
  • the application is served with django
  • hatebase database for detecting hate speeches and words
  • our own database and duck duck go search for checking content credibility
  • javascript for interactive content on the webpage and for the chrome extension
  • twitter, facebook and reddit api for retrieving content
  • wikidata and sparql for fetching information about politicians

Challenges we ran into

  • Facts checking is tremendously hard
  • website credibility
  • hate speech analysis is not just single words checking
  • wikidata querying is not easy and can take a while
  • parsing and scrapping websites and search engines results
  • Not enough time to work on our own classifier, even though we have annotated data

Accomplishments that we're proud of

  • Good looking web application that works
  • the chrome extension is simple but effective
  • working hate speech detection

What we learned

  • generating and using apis
  • using and combining multiple content sources
  • generating meaningful visualizations
  • building chrome extension

What's next for HackHate

  • Getting a large dataset from reddit data and training our own machine learning classifier
  • Extending our database for credibility checking
  • annotating the web pages with chrome extension to give live credibility checking
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