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

被引:12
作者
Zayet, Tasnim M. A. [1 ]
Ismail, Maizatul Akmar [1 ]
Varathan, Kasturi Dewi [1 ]
Noor, Rafidah M. D. [2 ]
Chua, Hui Na [3 ]
Lee, Angela [3 ]
Low, Yeh Ching [3 ]
Singh, Sheena Kaur Jaswant [4 ]
机构
[1] Univ Malaya, Dept Informat Syst, Kuala Lumpur, Malaysia
[2] Univ Malaya, Dept Comp Syst & Technol, Kuala Lumpur, Malaysia
[3] Sunway Univ, Dept Comp & Informat Syst, Petaling Jaya, Selangor, Malaysia
[4] Univ Malaya, Fac Languages & Linguist, Dept English Language, Kuala Lumpur, Malaysia
关键词
Intelligent transportation system; Traffic; Opinion mining; Text mining; Social media analysis; Systematic mapping review; Sentiment analysis; SENTIMENT ANALYSIS; PUBLIC-TRANSIT; TWITTER; QUALITY; OPPORTUNITIES; PERCEPTIONS; FRAMEWORK; ADOPTION; TRAVEL;
D O I
10.1007/s11192-021-04046-2
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页码:6383 / 6421
页数:39
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