New Disasters in the Twittersphere: How Communities Utilize Social Media to Seek and Share Information in the Wake of Induced Seismicity

Tracy, Andrew; Klucik, Rudy; Javernick‐Will, Amy; Poleacovschi, Cristina

doi:10.1061/9780784481288.051

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…In the first step, due to its unique properties as a mixed social and information network (Wang et al, 2020), data availability and convenience of data gathering (Klašnja et al, 2017), Twitter was chosen as the social media platform for this study. Also, Twitter was chosen over other social networks because the majority of Twitter data is publicly accessible and the developer interface is more conducive to the type of code required to mine the data required to represent the networks of a community (Tracy et al, 2018). Twitter accounts function as "microblogs" in which users can view the tweets of other users and direct their own posts to other users (Tracy et al, 2018).…”

Section: Methodsmentioning

confidence: 99%

“…Also, Twitter was chosen over other social networks because the majority of Twitter data is publicly accessible and the developer interface is more conducive to the type of code required to mine the data required to represent the networks of a community (Tracy et al , 2018). Twitter accounts function as “microblogs” in which users can view the tweets of other users and direct their own posts to other users (Tracy et al , 2018). In the Philippines, the most used social media platforms include YouTube (97.2%), Facebook (96.8%), Facebook Messenger (92.1%), Instagram (73.4%), Twitter (62.7%), Tiktok (48.8%), Pinterest (39.1%), Viber (36.9%), Skype (36.7%), Linkedin (36.4%), Snapchat (33.8%), WhatsApp (30.9%), Reddit (27%), Telegram (22%), WeChat (21.3%) and Tumblr (18.9%) (Kepios, 2021).…”

Section: Methodsmentioning

confidence: 99%

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Social media sensing framework for urban infrastructure management: a Philippine case study

Tien¹,

Nguyen²,

Banlasan³

2023

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Purpose This study aims to use social media data mining to revitalize and support existing urban infrastructure monitoring strategies by extracting valuable insights from public opinion, as current strategies struggle with issues such as adaptability to changing conditions, public engagement and cost effectiveness. Design/methodology/approach Twitter messages or “Tweets” about public infrastructure in the Philippines were gathered and analyzed to discover reoccurring concerns in public infrastructure, emerging topics in public debates and the people’s general view of infrastructure services. Findings This study proposes a topic model for extracting dominating subjects from aggregated social media data, as well as a sentiment analysis model for determining public opinion sentiment toward various urban infrastructure components. Originality/value The findings of this study highlight the potential of social media data mining to go beyond the limitations of traditional data collection techniques, as well as the importance of public opinion as a key driver for more user-involved infrastructure management and as an important social aspect that can be used to support planning and response strategies in routine maintenance, preservation and improvement of urban infrastructure systems.

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