IEEE Access (Jan 2023)

A Citizen Science Approach for Analyzing Social Media With Crowdsourcing

  • Carlo Bono,
  • Mehmet Oguz Mulayim,
  • Cinzia Cappiello,
  • Mark James Carman,
  • Jesus Cerquides,
  • Jose Luis Fernandez-Marquez,
  • Maria Rosa Mondardini,
  • Edoardo Ramalli,
  • Barbara Pernici

DOI
https://doi.org/10.1109/ACCESS.2023.3243791
Journal volume & issue
Vol. 11
pp. 15329 – 15347

Abstract

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Social media have the potential to provide timely information about emergency situations and sudden events. However, finding relevant information among the millions of posts being added every day can be difficult, and in current approaches developing an automatic data analysis project requires time and technical skills. This work presents a new approach for the analysis of social media posts, based on configurable automatic classification combined with Citizen Science methodologies. The process is facilitated by a set of flexible, automatic and open-source data processing tools called the Citizen Science Solution Kit. The kit provides a comprehensive set of tools that can be used and personalized in different situations, particularly during natural emergencies, starting from images and text contained in the posts. The tools can be employed by citizen scientists for filtering, classifying, and geolocating the content with a human-in-the-loop approach to support the data analyst, including feedback and suggestions on how to configure the automated tools, and techniques to gather inputs from citizens. Using flooding scenario as a guiding example, this paper illustrates the structure and functioning of the different tools proposed to support citizens scientists in their projects, and a methodological approach to their use. The process is then validated by discussing three case studies based on the Albania earthquake of 2019, the Covid-19 pandemic, and the Thailand floods of 2021. The results suggest that a flexible approach to tools composition and configuration can support a timely setup of an analysis project by citizen scientists, especially in case of emergencies in unexpected locations.

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