What to Expect When the Unexpected Happens: Social Media Communications Across Crises

By Alexandra Olteanu, Sarah Vieweg, Carlos Castillo. 2015

523 citations recorded by the source corpus.

The use of social media to communicate timely information during crisis situations has become a common practice in recent years. In particular, the one-to-many nature of Twitter has created an opportunity for stakeholders to disseminate crisis-relevant messages, and to access vast amounts of information they may not otherwise have. Our goal is to understand what affected populations, response agencies and other stakeholders can expect-and not expect-from these data in various types of disaster situations. Anecdotal evidence suggests that different types of crises elicit different reactions from Twitter users, but we have yet to see whether this is in fact the case. In this paper, we investigate several crises-including natural hazards and human-induced disasters-in a systematic manner and with a consistent methodology. This leads to insights about the prevalence of different information types and sources across a variety of crisis situations.

Subfields: Communication, Sociology and Political Science, Statistical and Nonlinear Physics

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Citations in the corpus

Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019, background): “…them, but also what they say (Olteanu et al., 2017b); just as the characteristics of crisis events leave a distinctive “print” on social media with respect to time and duration, including variations in the kind of information being posted and by whom (Saleem et al., 2014; Olteanu et al., 2015).”
Hate Lingo: A Target-based Linguistic Analysis of Hate Speech in Social Media (2018, background): “On one hand, it enables people to share information, provides a framework for support during a crisis (Olteanu, Vieweg, and Castillo 2015), aids law enforcement agencies (Crump 2011) and more generally facilitates insight into society at large.”
Twitter as a Lifeline: Human-annotated Twitter Corpora for NLP of Crisis-related Messages (2016, background): “Despite there exists some resources e.g. (Temnikova et al., 2015; Olteanu et al., 2015), however, due to the scarcity of relevant data, in particular human-annotated data, crisis in-formatics researchers still cannot fully utilize the capabilities of different computational methods.”
When Are Search Completion Suggestions Problematic? (2020, methodology): “Then, following common practices in thematic analysis [1, 7, 61], we iteratively merged related concepts mentioned across the various threads of literature in a bottom-up fashion.”
CrisisMMD: Multimodal Twitter Datasets from Natural Disasters (2018, background): “In another work (Olteanu, Vieweg, and Castillo 2015), the authors provide a dataset that consists of tweets from 26 crisis events that took place between 2012 and 2013.”
Processing Social Media Messages in Mass Emergency (2014, background): “We also remark that different types of disaster elicit different distributions of messages [Olteanu et al. 2015].”
From classification to quantification in tweet sentiment analysis (2016, background): “…tweet classiﬁcation are the real goal in Asur and Huberman (2010), which analyses Twitter data in order to predict box ofﬁce revenues for movies; in Olteanu et al. (2015), whose authors try to determine the percentage of tweets that are about infrastructure damage vs. those which are about…”
Distilling the Outcomes of Personal Experiences: A Propensity-scored Analysis of Social Media (2017, background): “People do this for many reasons [30, 51, 57, 71, 74]: keeping in touch with friends, gaining social capital, or even helping others.”