Leveraging VOSviewer approach for mapping, visualisation, and interpretation of crisis data for disaster management and decision-making
Analysing social media data is crucial for crisis management organisations to make timely decisions. Researchers in crisis informatics have devised various methods and systems to process and classify large volumes of crisis-related social media data for effective crisis response and recovery. Howeve...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-06-01
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| Series: | International Journal of Information Management Data Insights |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667096824001034 |
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| author | Umar Ali Bukar Md Shohel Sayeed Oluwatosin Ahmed Amodu Siti Fatimah Abdul Razak Sumendra Yogarayan Mohamed Othman |
| author_facet | Umar Ali Bukar Md Shohel Sayeed Oluwatosin Ahmed Amodu Siti Fatimah Abdul Razak Sumendra Yogarayan Mohamed Othman |
| author_sort | Umar Ali Bukar |
| collection | DOAJ |
| description | Analysing social media data is crucial for crisis management organisations to make timely decisions. Researchers in crisis informatics have devised various methods and systems to process and classify large volumes of crisis-related social media data for effective crisis response and recovery. However, the complexity of previous solutions hampers the timely processing of this data, its visualisation, and its interpretation, which is necessary for effective crisis response. Hence, this study addresses this challenge by employing visualisation of similarities to analyse and visualise crisis datasets to aid crisis management and decision-making. The results reveal a ''nine-cluster community” of relevant keywords comprising “Green, Brown, Red, Blue, Pink, Purple, Yellow, Orange, and Cyan” colours, in both binary and full count. Specifically, the findings reveal various keywords such as the needs for food, water, shelter, medicine, and electricity. Thereafter, the study discusses the implications of VOSviewer for analysing crisis data theoretically and practically. |
| format | Article |
| id | doaj-art-7373ee18a7f044c495e4f4b80b9fd477 |
| institution | Kabale University |
| issn | 2667-0968 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Information Management Data Insights |
| spelling | doaj-art-7373ee18a7f044c495e4f4b80b9fd4772025-08-20T03:45:44ZengElsevierInternational Journal of Information Management Data Insights2667-09682025-06-015110031410.1016/j.jjimei.2024.100314Leveraging VOSviewer approach for mapping, visualisation, and interpretation of crisis data for disaster management and decision-makingUmar Ali Bukar0Md Shohel Sayeed1Oluwatosin Ahmed Amodu2Siti Fatimah Abdul Razak3Sumendra Yogarayan4Mohamed Othman5Centre for Intelligent Cloud Computing (CICC), Faculty of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, Bukit Beruang, 75450 Melaka, Malaysia; Corresponding authors.Centre for Intelligent Cloud Computing (CICC), Faculty of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, Bukit Beruang, 75450 Melaka, Malaysia; Corresponding authors.Department of Electrical, Electronics and System Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, MalaysiaCentre for Intelligent Cloud Computing (CICC), Faculty of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, Bukit Beruang, 75450 Melaka, MalaysiaCentre for Intelligent Cloud Computing (CICC), Faculty of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, Bukit Beruang, 75450 Melaka, MalaysiaDepartment of Communication Technology and Network, Universiti Putra Malaysia. 43400 UPM Serdang Selangor Malaysia; Laboratory of Computational Science and Mathematical Physics, Institute for Mathematical Research, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, MalaysiaAnalysing social media data is crucial for crisis management organisations to make timely decisions. Researchers in crisis informatics have devised various methods and systems to process and classify large volumes of crisis-related social media data for effective crisis response and recovery. However, the complexity of previous solutions hampers the timely processing of this data, its visualisation, and its interpretation, which is necessary for effective crisis response. Hence, this study addresses this challenge by employing visualisation of similarities to analyse and visualise crisis datasets to aid crisis management and decision-making. The results reveal a ''nine-cluster community” of relevant keywords comprising “Green, Brown, Red, Blue, Pink, Purple, Yellow, Orange, and Cyan” colours, in both binary and full count. Specifically, the findings reveal various keywords such as the needs for food, water, shelter, medicine, and electricity. Thereafter, the study discusses the implications of VOSviewer for analysing crisis data theoretically and practically.http://www.sciencedirect.com/science/article/pii/S2667096824001034Co-occurrence networksData analysisDecision-making;Disaster managementSocial mediaVisualisationVOSviewer |
| spellingShingle | Umar Ali Bukar Md Shohel Sayeed Oluwatosin Ahmed Amodu Siti Fatimah Abdul Razak Sumendra Yogarayan Mohamed Othman Leveraging VOSviewer approach for mapping, visualisation, and interpretation of crisis data for disaster management and decision-making International Journal of Information Management Data Insights Co-occurrence networks Data analysis Decision-making;Disaster management Social media Visualisation VOSviewer |
| title | Leveraging VOSviewer approach for mapping, visualisation, and interpretation of crisis data for disaster management and decision-making |
| title_full | Leveraging VOSviewer approach for mapping, visualisation, and interpretation of crisis data for disaster management and decision-making |
| title_fullStr | Leveraging VOSviewer approach for mapping, visualisation, and interpretation of crisis data for disaster management and decision-making |
| title_full_unstemmed | Leveraging VOSviewer approach for mapping, visualisation, and interpretation of crisis data for disaster management and decision-making |
| title_short | Leveraging VOSviewer approach for mapping, visualisation, and interpretation of crisis data for disaster management and decision-making |
| title_sort | leveraging vosviewer approach for mapping visualisation and interpretation of crisis data for disaster management and decision making |
| topic | Co-occurrence networks Data analysis Decision-making;Disaster management Social media Visualisation VOSviewer |
| url | http://www.sciencedirect.com/science/article/pii/S2667096824001034 |
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