DiscoverText is sponsoring a student data challenge on “fake” news detection using a corpus of 20 million “Trump” Tweets collected between April and August 2016.
– Build a model of fake news on Twitter
– Submit the model using a short video (=<60 seconds)
– Teams must use our dataset and online collaborative tools, which we will provide for free.
– Data export is prohibited.
– The model must focus on the nature and scope of fake news itself, not external analyses of it.
– Qualitative, quantitative, and mixed methods models are all welcome.
– Collaborative teams must include 2 or 3 students at any educational institution.
– Faculty supervisors may join one or more teams.
– The challenge is open to students in any country.
– The final report simply needs to be in English.
– Entry Deadline is now extended to April 1, 2017
– See Video Update #1 about the data samples
– Links to videos presenting the model in 60 seconds or less on YouTube must be Tweeted with the hashtag #fakenewsdetection.
1st Prize: $100 for each student.
2nd Prize: $50 for each student.
3rd Prize: $25 for each student.
Every team that submits a video will retain an academic DiscoverText license for the remainder of 2017.
There are many ways to explore the metadata, Tweet text data, images, news links (both fake and real), to test and refine student hunches about the scope and nature of fake news disseminated on Twitter. Our goal is to share these models with academic research community and to support a variety of methodologies for human or automated fake news detection. There is no a priori labeled data or ground truth. Everyone gets the same unlabeled data and the same tools to build models. Everyone builds their own models. Anyone can collaborate with anyone else on the system (not restricted to your team). How you define and deliver the model is entirely up to you. We have no idea what fake news is…yet. It seems to mean a lot of different things to different people. We are looking for models that make sense to most people.
– Have each member of the team sign up for a free trial DiscoverText account.
– Send an email to email@example.com with your team name and a list of team member names and emails.
– Identify a student team leader who can manage the project and serve as a point of contact.
– Schedule a web meeting to go over some of the e-discovery, human coding, and machine-learning techniques.
– Review the DiscoverText help guides and FAQs: https://texifter.zendesk.com/hc/en-us
– Check out some use cases and methods in previous scholarly mentions of DiscoverText.
For more information, contact us at firstname.lastname@example.org.