Temporal network analysis of inter-organizational communications on social media during disasters: A study of Hurricane Harvey in Houston

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Abstract

The objective of this study is to model and analyze inter-organizational communication networks on social media to characterize the roles of organizations and situational information communication before, during and after disasters. Recent studies have shown that social media plays an important role in disasters, offering a participatory, collaborative and self-organized structure to communicate and disseminate situational information. Despite growing research on social media during disasters, little is known about the dynamic properties of inter-organizational networks and the roles of different organizations in communication networks on social media during disasters. This understanding is important for evaluating and improving collective action for disaster preparedness, emergency response, and recovery. To address this gap, this study presents a methodology for mapping and analyzing online organizational communication networks based on their interactions on twitter using the data obtained from Hurricane Harvey. The proposed method enables examining the network properties of online inter-organizational communication networks, unveiling the evolution of the roles of organizations within different phases of the disaster. The results show that: 1) during Harvey, government organizational users primarily generate information, while non-government organizational users mainly disseminate information, 2) during Harvey, most users in the cores of online organizational communication networks are from government organizations, 3) there are limited interactions among government and non-government organizational users before and after Harvey. The results provide insights into the roles of different types of organizations in online communication networks, helping make recommendations to improve inter-organizational communication in online social media to enhance disaster preparedness, responses, and recovery.

Introduction

Social media (such as Twitter and Facebook) have become a new form of infrastructure for communities in coping with disasters [1,2]. Social media enable timely communication and understanding of situational information. Also, social media offer a participatory, collaborative, and self-organized structure for emergency response and public warning during disasters [[3], [4], [5], [6]]. Accordingly, mapping, modeling and analyzing social media data could provide insights into the network dynamics of inter-organizational communications prior, during, and after a disaster. Understanding the inter-organizational communication networks on online social media is an important step for improving collective action related to hazard communication and public warning among various organizations. Aldrich and Meyer [7] defined links between organizations and links between citizens and organizations as important parts of social capital that have a great contribution to community resilience. Organizations (including government and non-government organizations) conduct and execute emergency responses, and their network interactions would have great impacts on disaster response and post-disaster recovery [[8], [9], [10]]. Recognizing this, many studies have examined inter-organizational communication and coordination during emergency response. For example, Harris [11] studied inter-organizational relationships during and after superstorm Sandy. The analysis identified emergent organizations that connected separate parts of the local stakeholder network, which plays an important role in emergency responses and post-Sandy recovery. Kapucu [12] studied inter-organizational coordination in emergency response to the September 11, 2001, terrorist attacks. The results showed that a well-coordinated inter-organizational network would greatly contribute to effective emergency responses and disaster recovery. These studies mapped and analyzed inter-organizational networks through the use of conventional methods such as surveys. The network models developed through organizational surveys have a major challenge regarding the inclusion of all relevant entities and communication links. With the increasing adoption of social media for communication in emergency response and public warning, there is an important need for characterizing the dynamics of inter-organizational communication networks on social media. However, as discussed in the following section, the existing literature related to social media in civil infrastructure and disaster research offers limited insight into the communication patterns and network properties among organizations during the course of a disaster. Hence, in this paper, we established a methodology to map, model and analyze the inter-organizational communication networks based on data from Twitter to evaluate three fundamental network properties (e.g., degree centrality, betweenness centrality, and core-periphery structure). The study utilized the Twitter data from the Houston area before, during and after Hurricane Harvey to study the evolution of communication patterns, network properties, and roles of organizations at different stages of the disaster.

Section snippets

Background and point of departure

The literature related to social media in disaster research is rapidly growing. Multiple studies, such as Zhang et al. [13]; have provided systematic literature reviews to highlight the state of the field and future directions. In this section, we briefly discuss some recent studies related to analyzing social media in civil infrastructure and disaster research to highlight the point of departure for this study. Twitter, in particular, has been studied extensively by researchers due to its ease

Data

We collected the data related to Hurricane Harvey through the Twitter PowerTrack application programming interface (API) from Gnip, a data provider. The data include the text of the tweets, posted time stamps, retweet/reply status, URLs to external sources, as well as user profile information such as user profession, locality, created time and follower count. To have a focus on the communication among organizations in a specific area, we defined a geographical boundary for geotagged tweets and

Methodology

To extract organizational accounts, map and analyze the inter-organizational communication networks on social media, we propose a three-step framework: (1) extract organization accounts in the dataset, (2) map online organizational communication networks based on twitter interactions among organizational accounts, and (3) conduct network analysis to get daily network properties including in-degree and out-degree centrality, betweenness centrality, and core-periphery structure. Fig. 2

Results

Based on the framework described in the previous section, we mapped the daily online organizational communication networks from August 22 to September 10 (some examples are illustrated in Fig. 3(a)~(f)). Fig. 3(g) shows the number of edges in correspondent daily networks. The weight of edges is the number of interactions between two organizational users on the same day. For example, if one organizational user retweets the post of another organizational user twice on the same day, the weight of

Discussion

The network properties of mapped online organizational communication networks reveal the situational roles of organizational users in online social media during disasters. The following discussion will focus on the evolution of organization roles before, during and after disasters, and the differences between the roles of different types of organizations. Based on the lessons learned from the results, we provide recommendations for organizational users to get better involvement and

Limitation

This study has some limitations. First, despite the best effort of the authors, the dataset might miss some important organizational users that played important roles in Hurricane Harvey such as USACE, Harris County Flood Control District (HCFCD), and FEMA. These organizational users were not included in the dataset because they do not have geographic information mentioned in the Houston area in their twitter biographies (e.g., HCFCD) or they are not physically located in the Houston area

Concluding remarks

This paper mapped and analyzed online organizational communication networks based on interactions among organizational users on Twitter to specify their roles during Hurricane Harvey. The study examined the communication networks and analyzed three network properties to study the roles of organizations in disasters. The findings provide empirical evidence regarding the extent to which different organizational users play a role in social media communications during disasters. With additional

Declaration of competing interest

The authors claim that there is no conflict of interest.

Acknowledgments

The authors would like to acknowledge funding support from the National Science Foundation CRISP project # (1832662): “Anatomy of Coupled Human-Infrastructure Systems Resilience to Urban Flooding: Integrated Assessment of Social, Institutional, and Physical Networks.” Publication supported in part by an Institutional Grant (NA18OAR4170088) to the Texas Sea Grant College Program from the National Sea Grant Office, National Oceanic and Atmospheric Administration, US Department of Commerce. This

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