Student Challenge on fake news detection

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.
The Challenge
– Build a model of fake news on Twitter
– Submit the model using a short video (=<60 seconds)
Requirements
– 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 March 1, 2017: Links to videos presenting the model in
60 seconds or less on YouTube must be Tweeted with the hashtag
#fakenewsdetection.
Prizes
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.
Background
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.
Start Here
– Have each member of the team sign up for a free trial DiscoverText
account.
– Send an email to info[at]discovertext.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.
Training
– 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:
– Check out some use cases and methods in previous scholarly mentions of
For more information, contact info[at]discovertext.com .

Об авторе Лидия Пивоварова

СПбГУ - старший преподаватель, University of Helsinki - PhD student http://philarts.spbu.ru/structure/sub-faculties/itah_phil/teachers/pivovarova
Запись опубликована в рубрике Ресурсы/Софт. Добавьте в закладки постоянную ссылку.

1 комментарий: Student Challenge on fake news detection

  1. DiscoverText говорит:

    Thanks for sharing the contest. Teams are still forming with over a month to go until the deadline. Here is an update: http://discovertext.com/2017/01/15/fake-news-detection-challenge-update/

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