A Community Perspective on Resilience Analytics: A Visual Analysis of Community Mood

López-Cuevas, Armando; Ramírez-Márquez, José Emmanuel; Sánchez-Ante, Gildardo; Barker, Kash

doi:10.1111/risa.12788

Cited by 26 publications

(12 citation statements)

References 39 publications

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“…Previous research has found similar levels of location reporting, with only up to about 3% of tweets contain geolocation information (Sloan & Morgan, 2015). Twitter has been selected in prior studies as a social media platform for examining aspects of resilience, such as emotional stability or collective solidarity (Garcia & Rimé, 2019; López‐Cuevas, Ramírez‐Márquez, Sanchez‐Ante, & Barker, 2017).…”

Section: Methodsmentioning

confidence: 99%

Expressions of Resilience: Social Media Responses to a Flooding Event

Anderson

2020

Risk Analysis

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Concerns over the resilience of individuals within communities impacted by extreme weather events have heightened in recent years due to the increasing frequency and intensity of these events. Individuals’ participation in communicative activities is an integral part of how they prepare for and respond to natural disasters. This study focuses on how individuals express resilience in social media posts from Twitter before, during, and after a regional flooding event in Colorado in 2013 (N = 210,303). Findings show that both negative and positive emotional responses spike at the start of the event, with positive emotions remaining high in the weeks following the event. Uses of language related to social connections, as well as references to home and work, increased during and after the event. Tweets used pronouns focused on the self during the event but shifted to pronouns focused on the collective after the event. This study points the importance of language for understanding the lasting impact extreme weather events can have on individuals, as well as when and how to reach individuals with information about recovery. The increased focus on collective language after the event provides an opportunity for calls to action in collecting and distributing shared resources.

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Section: Methodsmentioning

confidence: 99%

Expressions of Resilience: Social Media Responses to a Flooding Event

Anderson

2020

Risk Analysis

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“…Another thrust of social media analytics is an analysis of tweet content, in which a semantic understanding of a tweet is used to make assessments of the tweet author [22]. Related to disasters, the 'mood' of tweets was tracked through multiple disasters affecting North America as a proxy for how individuals recover psychologically from disasters [30]. Other analyses use the content of social media networks to understand the patterns of information diffusion in disaster [31].…”

Section: B Twittermentioning

confidence: 99%

Twitter and Disasters: A Social Resilience Fingerprint

2019

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Understanding the resilience of a community facing a crisis event is critical to improving its adaptive capacity. Community resilience has been conceptualized as a function of the resilience of components of a community such as ecological, infrastructure, economic, and social systems, etc. In this paper, we introduce the concept of a ''resilience fingerprint'' and propose a multi-dimensional method for analyzing components of community resilience by leveraging existing definitions of community resilience with data from the social network Twitter. Twitter data from 14 events are analyzed and their resulting resilience fingerprints computed. We compare the fingerprints between events and show that major disasters such as hurricanes and earthquakes have a unique resilience fingerprint which is consistent between different events of the same type. Specifically, hurricanes have a distinct fingerprint which differentiates them from other major events. We analyze the components underlying the similarity among hurricanes and find that ecological, infrastructure and economic components of community resilience are the primary drivers of the difference between the community resilience of hurricanes and other major events.INDEX TERMS Data analysis, human computer interaction, resilience, Twitter.

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“…It has been shown that changes in the mood of social networks can be correlated to economic trends, public demonstrations, and political reactions, among others. Lopez-Cuevas et al (25) describe a new methodology to analyze mood as a proxy of behavior and how disruptive events (both positive and negative) can affect different populations in situations of risk. The methodology encompasses three perspectives: (i) understanding the general behavior of a population by harvesting big data from different social media sources (Twitter in particular), (2) developing visual analytics to contrast the internal and external behavior of a community (through what the authors term a similarity matrix), and (3) identifying relevant events as the sources of disruption.…”

Section: Eissmentioning

confidence: 99%

Advances in Risk Analysis with Big Data

Choi

Lambert

2017

Risk Analysis

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With cloud computing, Internet-of-things, wireless sensors, social media, fast storage and retrieval, etc., organizations and enterprises have access to unprecedented amounts and varieties of data. Current risk analysis methodology and applications are experiencing related advances and breakthroughs. For example, highway operations data are readily available, and making use of them reduces risks of traffic crashes and travel delays. Massive data of financial and enterprise systems support decision making under risk by individuals, industries, regulators, etc. In this introductory article, we first discuss the meaning of big data for risk analysis. We then examine recent advances in risk analysis with big data in several topic areas. For each area, we identify and introduce the relevant articles that are featured in the special issue. We conclude with a discussion on future research opportunities.

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A Community Perspective on Resilience Analytics: A Visual Analysis of Community Mood

Cited by 26 publications

References 39 publications

Expressions of Resilience: Social Media Responses to a Flooding Event

Expressions of Resilience: Social Media Responses to a Flooding Event

Twitter and Disasters: A Social Resilience Fingerprint

Advances in Risk Analysis with Big Data

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