Matching Items (14)
Filtering by
- All Subjects: Social Media
- Creators: Department of Management and Entrepreneurship
Description
Online social media is popular due to its real-time nature, extensive connectivity and a large user base. This motivates users to employ social media for seeking information by reaching out to their large number of social connections. Information seeking can manifest in the form of requests for personal and time-critical information or gathering perspectives on important issues. Social media platforms are not designed for resource seeking and experience large volumes of messages, leading to requests not being fulfilled satisfactorily. Designing frameworks to facilitate efficient information seeking in social media will help users to obtain appropriate assistance for their needs
and help platforms to increase user satisfaction.
Several challenges exist in the way of facilitating information seeking in social media. First, the characteristics affecting the user’s response time for a question are not known, making it hard to identify prompt responders. Second, the social context in which the user has asked the question has to be determined to find personalized responders. Third, users employ rhetorical requests, which are statements having the
syntax of questions, and systems assisting information seeking might be hindered from focusing on genuine questions. Fouth, social media advocates of political campaigns employ nuanced strategies to prevent users from obtaining balanced perspectives on
issues of public importance.
Sociological and linguistic studies on user behavior while making or responding to information seeking requests provides concepts drawing from which we can address these challenges. We propose methods to estimate the response time of the user for a given question to identify prompt responders. We compute the question specific social context an asker shares with his social connections to identify personalized responders. We draw from theories of political mobilization to model the behaviors arising from the strategies of people trying to skew perspectives. We identify rhetorical questions by modeling user motivations to post them.
and help platforms to increase user satisfaction.
Several challenges exist in the way of facilitating information seeking in social media. First, the characteristics affecting the user’s response time for a question are not known, making it hard to identify prompt responders. Second, the social context in which the user has asked the question has to be determined to find personalized responders. Third, users employ rhetorical requests, which are statements having the
syntax of questions, and systems assisting information seeking might be hindered from focusing on genuine questions. Fouth, social media advocates of political campaigns employ nuanced strategies to prevent users from obtaining balanced perspectives on
issues of public importance.
Sociological and linguistic studies on user behavior while making or responding to information seeking requests provides concepts drawing from which we can address these challenges. We propose methods to estimate the response time of the user for a given question to identify prompt responders. We compute the question specific social context an asker shares with his social connections to identify personalized responders. We draw from theories of political mobilization to model the behaviors arising from the strategies of people trying to skew perspectives. We identify rhetorical questions by modeling user motivations to post them.
ContributorsRanganath, Suhas (Author) / Liu, Huan (Thesis advisor) / Lai, Ying-Cheng (Thesis advisor) / Tong, Hanghang (Committee member) / Vaculin, Roman (Committee member) / Arizona State University (Publisher)
Created2017
Description
The pervasive use of social media gives it a crucial role in helping the public perceive reliable information. Meanwhile, the openness and timeliness of social networking sites also allow for the rapid creation and dissemination of misinformation. It becomes increasingly difficult for online users to find accurate and trustworthy information. As witnessed in recent incidents of misinformation, it escalates quickly and can impact social media users with undesirable consequences and wreak havoc instantaneously. Different from some existing research in psychology and social sciences about misinformation, social media platforms pose unprecedented challenges for misinformation detection. First, intentional spreaders of misinformation will actively disguise themselves. Second, content of misinformation may be manipulated to avoid being detected, while abundant contextual information may play a vital role in detecting it. Third, not only accuracy, earliness of a detection method is also important in containing misinformation from being viral. Fourth, social media platforms have been used as a fundamental data source for various disciplines, and these research may have been conducted in the presence of misinformation. To tackle the challenges, we focus on developing machine learning algorithms that are robust to adversarial manipulation and data scarcity.
The main objective of this dissertation is to provide a systematic study of misinformation detection in social media. To tackle the challenges of adversarial attacks, I propose adaptive detection algorithms to deal with the active manipulations of misinformation spreaders via content and networks. To facilitate content-based approaches, I analyze the contextual data of misinformation and propose to incorporate the specific contextual patterns of misinformation into a principled detection framework. Considering its rapidly growing nature, I study how misinformation can be detected at an early stage. In particular, I focus on the challenge of data scarcity and propose a novel framework to enable historical data to be utilized for emerging incidents that are seemingly irrelevant. With misinformation being viral, applications that rely on social media data face the challenge of corrupted data. To this end, I present robust statistical relational learning and personalization algorithms to minimize the negative effect of misinformation.
The main objective of this dissertation is to provide a systematic study of misinformation detection in social media. To tackle the challenges of adversarial attacks, I propose adaptive detection algorithms to deal with the active manipulations of misinformation spreaders via content and networks. To facilitate content-based approaches, I analyze the contextual data of misinformation and propose to incorporate the specific contextual patterns of misinformation into a principled detection framework. Considering its rapidly growing nature, I study how misinformation can be detected at an early stage. In particular, I focus on the challenge of data scarcity and propose a novel framework to enable historical data to be utilized for emerging incidents that are seemingly irrelevant. With misinformation being viral, applications that rely on social media data face the challenge of corrupted data. To this end, I present robust statistical relational learning and personalization algorithms to minimize the negative effect of misinformation.
ContributorsWu, Liang (Author) / Liu, Huan (Thesis advisor) / Tong, Hanghang (Committee member) / Doupe, Adam (Committee member) / Davison, Brian D. (Committee member) / Arizona State University (Publisher)
Created2019
Description
Incidents relating to professional/collegiate athletes and their use of social media have been a prominent topic in the news for the last several years. For collegiate athletes, a distasteful, offensive post can have a substantial impact on the rest of their lives, as he/she can have scholarships revoked, legal action taken upon them, and professional offers cut. An athlete's poor actions will affect their brand image and that of the school whose uniform they wear. Outcry over these incidents have caused teams, themselves, to compensate in a variety of ways. The following thesis is a narrative representation of these incidents, resulting outcry, and desperate compensation. The narrative touches upon the impact social media can have on a team, athletic department, and university. It explores the rules/restrictions of social media, marketing concepts such as branding, the right to free speech, and the impact/consequences of bad choices. The narrative is preceded and followed by analysis of real-world examples to provide sound rationale for the actions taken in the narrative.
ContributorsBornhoft, Holly Marie (Author) / Eaton, John (Thesis director) / Mokwa, Michael (Committee member) / Department of Marketing (Contributor) / Department of Management and Entrepreneurship (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Cyberbullying is a phenomenon which negatively affects individuals. Victims of the cyberbullying suffer from a range of mental issues, ranging from depression to low self-esteem. Due to the advent of the social media platforms, cyberbullying is becoming more and more prevalent. Traditional mechanisms to fight against cyberbullying include use of standards and guidelines, human moderators, use of blacklists based on profane words, and regular expressions to manually detect cyberbullying. However, these mechanisms fall short in social media and do not scale well. Users in social media use intentional evasive expressions like, obfuscation of abusive words, which necessitates the development of a sophisticated learning framework to automatically detect new cyberbullying behaviors. Cyberbullying detection in social media is a challenging task due to short, noisy and unstructured content and intentional obfuscation of the abusive words or phrases by social media users. Motivated by sociological and psychological findings on bullying behavior and its correlation with emotions, we propose to leverage the sentiment information to accurately detect cyberbullying behavior in social media by proposing an effective optimization framework. Experimental results on two real-world social media datasets show the superiority of the proposed framework. Further studies validate the effectiveness of leveraging sentiment information for cyberbullying detection.
ContributorsDani, Harsh (Author) / Liu, Huan (Thesis advisor) / Tong, Hanghang (Committee member) / He, Jingrui (Committee member) / Arizona State University (Publisher)
Created2017
Description
Marketing In The Digital Age, or MITDA is a start-up business that provides seminars and lectures on digital media marketing and social media algorithms to ASU students and small businesses. We work with social media influencers to host lectures and seminars on brand awareness at ASU, and then offer classes and consulting to small-businesses who are looking to expand their online brand awareness. The content that we focus on compromises many different aspects of digital media marketing: platform specific algorithms, trends, digital media content creation (such as Photoshop and Canva), influencer brand deals and sponsorships, and influencer consultations. With MITDA, ASU students and small businesses have the opportunity to hop on quick trends, build a marketable brand to Generation Z, and learn how to stay relevant in the new marketing world of influencers and content creators.
ContributorsOchsmann, Reagan (Author) / Byrne, Jared (Thesis director) / Larsen, Wiley (Committee member) / Barrett, The Honors College (Contributor) / Department of Management and Entrepreneurship (Contributor) / Department of Supply Chain Management (Contributor)
Created2023-05
Description
The Winner's Circle aims to provide a digital platform for sports fans and betting addicts, in hopes to help centralize various forms of social communication between family, close friends, and strangers alike. As the legalization of sports related gambling activities become more widespread throughout the United States as well as the rest of the world, our platform has to potential to connect millions of like-minded, adrenaline-seeking fans across the globe.
ContributorsPoremba, Charles (Author) / Sklar, Jack (Co-author) / Mauri, Angelo (Co-author) / Kenehan, Nicholas (Co-author) / Byrne, Jared (Thesis director) / Swader, Melissa (Committee member) / Smith, Keaton (Committee member) / Barrett, The Honors College (Contributor) / Department of Supply Chain Management (Contributor) / Department of Management and Entrepreneurship (Contributor)
Created2023-05
Description
The Winner's Circle aims to provide a digital platform for sports fans and betting addicts, in hopes to help centralize various forms of social communication between family, close friends, and strangers alike. As the legalization of sports related gambling activities become more widespread throughout the United States as well as the rest of the world, our platform has to potential to connect millions of like-minded, adrenaline-seeking fans across the globe.
ContributorsPoremba, Charles (Author) / Sklar, Jack (Co-author) / Mauri, Angelo (Co-author) / Kenehan, Nicholas (Co-author) / Byrne, Jared (Thesis director) / Swader, Melissa (Committee member) / Smith, Keaton (Committee member) / Barrett, The Honors College (Contributor) / Department of Supply Chain Management (Contributor) / Department of Management and Entrepreneurship (Contributor)
Created2023-05
Description
The Winner's Circle aims to provide a digital platform for sports fans and betting addicts, in hopes to help centralize various forms of social communication between family, close friends, and strangers alike. As the legalization of sports related gambling activities become more widespread throughout the United States as well as the rest of the world, our platform has to potential to connect millions of like-minded, adrenaline-seeking fans across the globe.
ContributorsPoremba, Charles (Author) / Sklar, Jack (Co-author) / Mauri, Angelo (Co-author) / Kenehan, Nicholas (Co-author) / Byrne, Jared (Thesis director) / Swader, Melissa (Committee member) / Smith, Keaton (Committee member) / Barrett, The Honors College (Contributor) / Department of Supply Chain Management (Contributor) / Department of Management and Entrepreneurship (Contributor)
Created2023-05
Description
The sports industry is unlike any other in that it connects individuals and consumers from destinations around the world with one common interest. That commonality can be as specific as a favorite player, team, league, or sport. All in all, it bands together entire communities with their passion for the game. American sports leagues such as the National Football League, National Hockey League, Major League Baseball, National Basketball Association, and many more, have all revolutionized the way that businesses view marketing though a user friendly, interactive, marketing tool with a universal reach.
ContributorsMarker, Sierra Kamalani Akiko (Author) / Eaton, John (Thesis director) / Lee, Christopher (Committee member) / Department of Management and Entrepreneurship (Contributor) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
The goal of Dough is to create financial content that educates college students and young adults in areas of financial literacy. College students and young adults generally have debt from student loans, and typically don’t have much time to work as they focus on school and earn their degree. Financial literacy can make the lives of young adults much easier, however this is typically not a resource that is easily available to them. Our proposed solution to fight the lack of financial literacy is to create educational content including videos, articles, and a website that educates students and young adults on how to acquire good financial habits.
ContributorsMitchell, Zachary (Author) / Gibson, Cole (Co-author) / Clausen, Taylor (Co-author) / Rodríguez, Natalia (Co-author) / Byrne, Jared (Thesis director) / Satpathy, Asish (Committee member) / Barrett, The Honors College (Contributor) / Department of Management and Entrepreneurship (Contributor)
Created2022-05