Corporate Sustainability Communication as ‘Fake News’: Firms’ Greenwashing on Twitter

Characterizing Political Fake News in Twitter by its Meta-Data

This article presents a preliminary approach towards characterizing political fake news on Twitter through the analysis of their meta-data. In particular, we focus on more than 1.5M tweets collected on the day of the election of Donald Trump as 45th president of the United States of America. We use the meta-data embedded within those tweets in order to look for differences between tweets contai...

Tweeting About Sustainability: Can Emotional Nowcasting Discourage Greewashing?

Fewer than 100 firms worldwide are recognised by Bloomberg to report accurate greenhouse gas emissions. Yet, tens of thousands of people are talking and tweeting about climate change every day. How can this attention be converted into accurate action? We propose that sustainable data science might help, specifically that ‘emotional nowcasting’ of societal responses to sustainability related sta...

Fake News in Social Networks

We model the spread of news as a social learning game on a network. Agents can either endorse or oppose a claim made in a piece of news, which itself may be either true or false. Agents base their decision on a private signal and their neighbors’ past actions. Given these inputs, agents follow strategies derived via multi-agent deep reinforcement learning and receive utility from acting in acco...

Influence of fake news in Twitter during the 2016 US presidential election

We investigate the influence of fake and traditional, fact-based, news outlets on Twitter during the 2016 US presidential election. Using a comprehensive dataset of 171 million tweets covering the five months preceding election day, we identify 30 million tweets, sent by 2.2 million users, which are classified as spreading fake and extremely biased news, based on a list of news outlets curated ...

The Economics of "Fake News"