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Investigating transportation research based on social media analysis: a systematic mapping review

Author

Listed:
  • Tasnim M. A. Zayet

    (University of Malaya)

  • Maizatul Akmar Ismail

    (University of Malaya)

  • Kasturi Dewi Varathan

    (University of Malaya)

  • Rafidah M. D. Noor

    (University of Malaya)

  • Hui Na Chua

    (Sunway University)

  • Angela Lee

    (Sunway University)

  • Yeh Ching Low

    (Sunway University)

  • Sheena Kaur Jaswant Singh

    (University of Malaya)

Abstract

Social media is a pool of users’ thoughts, opinions, surrounding environment, situation and others. This pool can be used as a real-time and feedback data source for many domains such as transportation. It can be used to get instant feedback from commuters; their opinions toward the transportation network and their complaints, in addition to the traffic situation, road conditions, events detection and many others. The problem is in how to utilize social media data to achieve one or more of these targets. A systematic review was conducted in the field of transportation-related research based on social media analysis (TRR-SMA) from the years between 2008 and 2018; 74 papers were identified from an initial set of 703 papers extracted from 4 digital libraries. This review will structure the field and give an overview based on the following grounds: activity, keywords, approaches, social media data and platforms and focus of the researches. It will show the trend in the research subjects by countries, in addition to the activity trends, platforms usage trend and others. Further analysis of the most employed approach (Lexicons) and data (text) will be also shown. Finally, challenges and future works are drawn and proposed.

Suggested Citation

  • Tasnim M. A. Zayet & Maizatul Akmar Ismail & Kasturi Dewi Varathan & Rafidah M. D. Noor & Hui Na Chua & Angela Lee & Yeh Ching Low & Sheena Kaur Jaswant Singh, 2021. "Investigating transportation research based on social media analysis: a systematic mapping review," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6383-6421, August.
    • Handle: RePEc:spr:scient:v:126:y:2021:i:8:d:10.1007_s11192-021-04046-2
    DOI: 10.1007/s11192-021-04046-2
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    References listed on IDEAS

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    1. Anna Kovacs-Gyori & Alina Ristea & Clemens Havas & Bernd Resch & Pablo Cabrera-Barona, 2018. "#London2012: Towards Citizen-Contributed Urban Planning Through Sentiment Analysis of Twitter Data," Urban Planning, Cogitatio Press, vol. 3(1), pages 75-99.
    2. Kim, Kun & Park, Oun-joung & Yun, Seunghyun & Yun, Haejung, 2017. "What makes tourists feel negatively about tourism destinations? Application of hybrid text mining methodology to smart destination management," Technological Forecasting and Social Change, Elsevier, vol. 123(C), pages 362-369.
    3. Xi Zhang & Yunjia Zhang & Senzhang Wang & Yuntao Yao & Binxing Fang & Philip S. Yu, 2018. "Improving Stock Market Prediction via Heterogeneous Information Fusion," Papers 1801.00588, arXiv.org.
    4. Gal-Tzur, Ayelet & Grant-Muller, Susan M. & Kuflik, Tsvi & Minkov, Einat & Nocera, Silvio & Shoor, Itay, 2014. "The potential of social media in delivering transport policy goals," Transport Policy, Elsevier, vol. 32(C), pages 115-123.
    5. Lee, Kiljae & Yu, Chunyan, 2018. "Assessment of airport service quality: A complementary approach to measure perceived service quality based on Google reviews," Journal of Air Transport Management, Elsevier, vol. 71(C), pages 28-44.
    6. N. Nima Haghighi & Xiaoyue Cathy Liu & Ran Wei & Wenwen Li & Hu Shao, 2018. "Using Twitter data for transit performance assessment: a framework for evaluating transit riders’ opinions about quality of service," Public Transport, Springer, vol. 10(2), pages 363-377, August.
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    Cited by:

    1. Tavishi Priyam & Tao Ruan & Qin Lv, 2023. "Demographic-Based Public Perception Analysis of Electric Vehicles on Online Social Networks," Sustainability, MDPI, vol. 16(1), pages 1-16, December.

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