Assessing Social Media Usage in Public Participation for Rapid Bus Transit Project Using Machine Learning

This paper aims to perform assessment of socialMedia usage, particularly Twitter, in public participation (PP) forInfrastructure projects in developing countries. The case of BusRapid Transit (BRT) of Jordan has been chosen as a case study.A comprehensive literature review was accomplished, followedby scraping the Arabic tweets relevant to the project. The tweetswere divided into three main periods, according to logical rea-soning as described in the paper. Tweets were then prepossessedincluding cleaning, tokenization, vectorization using AraBert toensure the highest contextualization for machine learning. Thefollowing analyses were performed: tweeting intensity, sentimentanalysis, tweets fluency and topic modeling. Findings of thisstudy reveals many difficulties associated with the public par-ticipation in the BRT project. The results indicated that lackof trust, appropriate communication and transparency createdlarge gap between the public and the project directors. Thisgap led to inappropriate public participation in the project, andconsequently high resistance as observed by the author. Findingsof the paper provide valuable insights for project managersand decision-makers. Understanding the public participationdimensions, the consequences of social media usage may improvepublic engagement and support the success of infrastructureprojects in developing countries like Jordan.