title: Sentinels of Breach: Lexical Choice as a Measure of Urgency in Social Media.
abstract: Objective This paper identifies general properties of language style in social media to help identify areas of need in disasters. Background In the search for metrics of need in social media data, much of the existing literature ignores processes of language usage. Psychological concepts, such as narrative breach, Gricean maxims, and lexical marking in cognition, may assist the recovery of disaster-relevant metrics from altered patterns of word prevalence. Method We analyzed several hundred thousand location-specific microblogs from Twitter for Hurricane Sandy, Oklahoma tornadoes, and the Boston Marathon bombing along with a fantasy football control corpus, examining the relative frequency of words in 36 antonym pairs. We compared the ratio of words within these pairs to the corresponding ratios recovered from an online word norm database. Results Partial rank correlation values between observed antonym ratios demonstrate consistent patterns across disasters. For Hurricane Sandy data, 25 antonym pairs have moderate to large effect sizes for discrepancies between observed and normative ratios. Across disasters, 7 pairs are stable and meet effect size criteria. Sentiment analysis, supplementary word frequency counts with respect to disaster proximity, and examples support a "breach" account for the observed results. Conclusion Lexical choice between antonyms, only somewhat related to sentiment, suggests that social media capture wide-ranging breaches of normal functioning. Application Antonym selection contributes to screening tools based on language style for identifying relevant content and quantifying disruption using social media without the a priori specification of content keywords.
authors.affiliation: Wright State University, Dayton, Ohio.
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Hampton
authors.affiliation: Wright State University, Dayton, Ohio.
authors.forename: Valerie L
authors.initials: VL
authors.lastname: Shalin
mesh_terms: D004189:Disaster Planning; D004190:Disasters / Q000706:statistics & numerical data*; D006801:Humans; D007802:Language; D011578:Psycholinguistics; D061108:Social Media / Q000706:statistics & numerical data*; D062206:Spatial Analysis; D009626:Terminology as Topic; D023481:Terrorism / Q000706:statistics & numerical data*; D014481:United States
keywords: disaster response; psycholinguistics