Twitter and perceptions of crisis-related stress

Abstract

The purpose of this research project is to determine which indicators might be present in social media data that could shed light on how populations cope with global crises, such as commodity price volatility or the continuing global economic crisis. As an initial investigation, this project was limited to the analysis of publicly available data from Twitter for July 2010 through October 2011. The work was further limited to tweets in Javanese/Bahasa Indonesia and English. The topics of focus included the affordability/availability of food, fuel, housing and loans. By classifying a populations’ tweets into several categories associated with relevant topics, it was possible to perform quantitative analysis to better understand populations’ vulnerabilities: detecting anomalies such as spikes or drops in the number of tweets about particular topics (e.g. comments about power outages in Indonesia or student loans in U.S.), observing weekly and monthly trends in Twitter conversations (e.g. discussions around debt in U.S.), finding patterns in the volume of particular topics over time (e.g. discussions around housing in U.S.), comparing the proportions of different sub-topics to understand shifts in trends over time (e.g. the ratio of tweets about formal loans vs. informal loans in Indonesia) or relating trends in Twitter conversations with external indicators (e.g. conversations around the price of rice in Indonesia mimicking the official inflation statistics). This research has pointed to the strong potential use of Twitter data for understanding the immediate worries, fears and concerns of populations, but at the same time, the research suggested that it is a poor source of data for gauging people’s long term aspirations. There are several remaining challenges, in particular that Twitter has a specific culture and demographic which needs to be better understood to strengthen any analysis of this type. Overall, this exploratory research shows some of the potential of Twitter data for exploring people’s perceptions of crisis-related stress and suggests research lines and methodologies for further investigations.

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