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.
","abstract_html":"<p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p>","abstract_has_math":false,"creators":["Bajarwan, Ahmad A."],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Engineering Management & Systems Engineering","degree_department":null,"school":null,"contributors":["Mamadou Seek","Ariel Pinto","Fatou Diouf"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-04-01T07:00:00Z","date_published":"2019-04-01T07:00:00Z","updated_at":"2026-07-24T03:34:53Z","subjects":["Infrastructure projects","Similarity","Stakeholder analysis","Stakeholder biases","Stakeholder managers","Communication Technology and New Media","Digital Communications and Networking","Social Media"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["9781392235393"],"render_values":[{"text":"9781392235393","href":null,"code":true}]}]},"links":{"outbound_url":"https://digitalcommons.odu.edu/emse_etds/142","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Mamadou Seek","Ariel Pinto","Fatou Diouf"]},{"key":"dc:creator","label":"Author","values":["Bajarwan, Ahmad A."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2020-06-04T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Engineering Management & Systems Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Infrastructure projects","Similarity","Stakeholder analysis","Stakeholder biases","Stakeholder managers","Communication Technology and New Media","Digital Communications and Networking","Social Media"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["9781392235393","https://digitalcommons.odu.edu/emse_etds/142"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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.
"]},{"key":"dc:title","label":"Title","values":["Evaluating Stakeholder Bias in Stakeholder Analysis In Social Media"]}]}],"canonical_facts":{"dc:contributor":["Mamadou Seek","Ariel Pinto","Fatou Diouf"],"dc:creator":["Bajarwan, Ahmad A."],"dc:date.available":["2020-06-04T07:00:00Z"],"dc:description.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.
"],"dc:identifier":["9781392235393","https://digitalcommons.odu.edu/emse_etds/142"],"dc:subject":["Infrastructure projects","Similarity","Stakeholder analysis","Stakeholder biases","Stakeholder managers","Communication Technology and New Media","Digital Communications and Networking","Social Media"],"dc:title":["Evaluating Stakeholder Bias in Stakeholder Analysis In Social Media"],"thesis:degree_discipline":["Engineering Management & Systems Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T03:34:53Z"}