Date of Award

Spring 2019

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Engineering Management & Systems Engineering

Committee Director

Mamadou Seek

Committee Member

Ariel Pinto

Committee Member

Fatou Diouf

Abstract

Stakeholder analysis is the first step in the planning of most infrastructure projects. Selecting and then applying the best method for a project’s stakeholder analysis is extremely important for correctly assessing stakeholder opinions. Social media platforms allow stakeholders to participate directly in analysis. However, as with most other analysis methods, social media introduces inherent biases.

Social media is a powerful tool for communication and networking, and it also provides a valuable source of information for analyzing user opinions about infrastructure projects. By using data collected from Twitter, analysts can create networks to represent connections among users, quantify their similarities, and then use those values to predict public opinion. We can also use this information to measure bias – that is, the impact the social media has on the opinions of its users.

Research and analysis show a correlation between user similarity and user opinion that indicates bias. Additionally, I observed that disagreement was stronger than agreement – if users disagreed, they would disagree strongly; if they agreed, they had varying levels of agreement strength. In other words, disagreement was fairly polarizing, but agreement tended not to invoke strong emotions one way or another.

The nearly universal use of social media is a powerful tool to both predict and shape public opinion. Stakeholder managers can predict stakeholder opinion by using their social network connections to determine conformity. And although social media has its own biases, its value as a data source for preliminary planning analysis should not be discounted.

DOI

10.25777/hsvb-kv43

ISBN

9781392235393

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