Investigating transportation research based on social media analysis: a systematic mapping review
Autor: | Tasnim M. A. Zayet, Angela Lee, Kasturi Dewi Varathan, Yeh Ching Low, Sheena Kaur Jaswant Singh, Rafidah M. D. Noor, Maizatul Akmar Ismail, Hui Na Chua |
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Rok vydání: | 2021 |
Předmět: |
Structure (mathematical logic)
Text mining Systematic mapping review Computer science 05 social sciences Sentiment analysis General Social Sciences Library and Information Sciences 050905 science studies Flow network Digital library Data science Article Field (computer science) Computer Science Applications Opinion mining Traffic Social media analysis Social media Intelligent transportation system 0509 other social sciences 050904 information & library sciences Set (psychology) |
Zdroj: | Scientometrics |
ISSN: | 1588-2861 0138-9130 |
DOI: | 10.1007/s11192-021-04046-2 |
Popis: | 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. Supplementary Information The online version contains supplementary material available at 10.1007/s11192-021-04046-2. |
Databáze: | OpenAIRE |
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