From airports to banks, healthcare, space crafts, and even amazon services, technology impacts almost every aspect of today’s life. If wrongdoings occur within or in relation to technology, they can have big implications on individuals, groups of people, or society as a whole. Whistleblowers are insiders who expose such wrongdoings— eventually stopping misconducts, such as fraud, endangerment to public health and safety, or damage to the environment. Twitter is a microblogging service that allows millions of users to share their views with people distributed all over the world on a daily basis. Tweets have the potential to contain useful information about whistleblowing in tech, from the general public and whistleblowers. However, until now this point has not been researched. To fill this gap, we conducted an exploratory study on technology-related whistleblowing tweets by manually analysing tweets, utilising descriptive statistics, and machine learning techniques. We mined 7,400 of tweets from whistleblowers themselves, as well as news and opinions about certain whistleblowers and whistleblowing cases. Although our results show that only 30% of the tweets in our sample dataset (obtained through specific search terms) contained relevant information about whistleblowing in technology, our analysis shows that tweets provide valuable information for both researchers and companies to understand the public opinion regarding whistleblowing cases. Furthermore, we found that machine learning techniques are promising means for extracting information about whistleblowing in tech from the vast stream of tweets.
Mon 15 MayDisplayed time zone: Hobart change
16:35 - 17:20 | Ethics & EnergyTechnical Papers / Registered Reports at Meeting Room 109 Chair(s): Arumoy Shome Delft University of Technology | ||
16:35 12mTalk | Energy Consumption Estimation of API-usage in Mobile Apps via Static Analysis Technical Papers Abdul Ali Bangash University of Alberta, Canada, Qasim Jamal FAST National University, Kalvin Eng University of Alberta, Karim Ali University of Alberta, Abram Hindle University of Alberta Pre-print | ||
16:47 12mTalk | An Exploratory Study on Energy Consumption of Dataframe Processing Libraries Technical Papers Pre-print | ||
16:59 6mTalk | Understanding issues related to personal data and data protection in open source projects on GitHub Registered Reports Anne Hennig Karlsruhe Institute of Technology, Lukas Schulte Universitity of Passau, Steffen Herbold University of Passau, Oksana Kulyk IT University of Copenhagen, Denmark, Peter Mayer University of Southern Denmark | ||
17:05 12mTalk | Whistleblowing and Tech on Twitter Technical Papers Laura Duits Vrije Universiteit Amsterdam, Isha Kashyap Vrije Universiteit Amsterdam, Joey Bekkink Vrije Universiteit Amsterdam, Kousar Aslam Vrije Universiteit Amsterdam, Emitzá Guzmán Vrije Universiteit Amsterdam |