Matching Items (13)
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- All Subjects: Social Media
- Creators: Ingram-Waters, Mary
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
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
Music can be an incredibly powerful tool, and in an age where technology allows us to connect with those that don’t live near us, finding ways to use music to encourage that bonding can be incredibly beneficial. Particularly, in a global pandemic such as COVID-19, finding ways to connect with others remotely is more important than ever. In this study, I will be looking at how one artist in particular, Tessa Violet, manages to continue to not only grow her community, but also encourage her community to bond with each other. She achieves this by finding various ways, unique to her and her branding, that allows her community to connect with each other. By using her platform to give scavenger hunts to her fanbase, promoting and fostering community growth through various platforms, and livestreaming in ways unique to her style, she is able to connect her audience with each other. By engaging and observing these various actions on her part, I am able to see and experience this community bonding myself. I also look at ways this might be able to expanded to other artists and their communities as well. The hope is that the internet and social media can be just another form of music encouraging people to connect with one another.
ContributorsPartin, Eli (Author) / Ingram-Waters, Mary (Thesis director) / Ring, Dan (Committee member) / Arts, Media and Engineering Sch T (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Sites of in-person fan/celebrity meetings can serve as a place for fans to share intimate details about themselves to celebrities. Through built-up confidence and knowledge of the subject matter, fans may be compelled to share personal anecdotes with the celebrity during these meetings. Fan studies scholars use the term “parasociality” to describe one-sided relationships between fans and celebrities. My research aims to show how in-person events cultivate intimacy between fans and celebrities, even while simultaneously reinforcing parasocial relationships. It is often used when referring to the relationships as being one-sided, even though the fan also gains something from the interaction.
ContributorsGalek, Veronica Lucya (Author) / Ingram-Waters, Mary (Thesis director) / Hsu, Emily (Committee member) / Schultz, Miranda (Committee member) / Walter Cronkite School of Journalism & Mass Comm (Contributor, Contributor) / School of Social Transformation (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
Description
The rise in social media usage has sparked a new marketing strategy for brands and entrepreneurs known as influencing. Influencers use marketing tactics to persuade their social media followers to purchase a certain brand. For this thesis, we will be focusing on micro influencers who are defined as people that began as a regular, everyday person and became known for their knowledge about some specialist niche with a range of 10,000-500,000 followers.
To conduct research, we developed a survey that was distributed and taken by students at Arizona State University. The goal of surveying college students was to understand how young people who regularly use social media are persuaded by micro-influencers. To gain more insight, we interviewed three local micro-influencers that we discovered through Instagram and research. The goal of these interviews was to discover tactics that micro-influencers use when posting to market sponsored products. Additionally, we hoped to uncover a pattern that micro-influencers use when building their social media following. Ultimately, we developed a six-step guide from our research that aspiring micro-influencers can follow to strategize their rise as a social media micro-influencer. We also discuss the social media app TikTok, which we believe will be heavily used by influencers and micro-influencers in the future.
To conduct research, we developed a survey that was distributed and taken by students at Arizona State University. The goal of surveying college students was to understand how young people who regularly use social media are persuaded by micro-influencers. To gain more insight, we interviewed three local micro-influencers that we discovered through Instagram and research. The goal of these interviews was to discover tactics that micro-influencers use when posting to market sponsored products. Additionally, we hoped to uncover a pattern that micro-influencers use when building their social media following. Ultimately, we developed a six-step guide from our research that aspiring micro-influencers can follow to strategize their rise as a social media micro-influencer. We also discuss the social media app TikTok, which we believe will be heavily used by influencers and micro-influencers in the future.
ContributorsPangburn, Morgan Lane (Co-author) / Harazim, Genevieve (Co-author) / Eaton, John (Thesis director) / Ingram-Waters, Mary (Committee member) / Department of Psychology (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
This project looks at the impact that the internet has had on society, and how it has shaped the way that digitally native generations live their lives. More specifically, this thesis showcases what it means for younger generations to be digitally native and how engaging with technology while growing up affects the way that these individuals experience contemporary adolescence. Generation X is said to be the last group of people to experience life before the spread of the personal computer and internet access. Newer generations, such as Generation Z, have grown up having constant and easy access to the internet, all of the information it encompasses, and its additional functions. This access has shaped much of the generation as individuals as well as society as a whole. It can be argued that the human experience has been fundamentally different for those born after the creation of the internet and the rapid increase in accessible technology that followed. Through an interview with a participant from Generation X, I will showcase the transformative role that the internet and technology has played in major life events for a digitally native individual compared to that of individuals from older generations. As a member of Generation Z, I will compare my personal narrative regarding ten different life events occurring between the ages of five to 25 that I feel are common and impactful to the narrative a of non-digitally native individual. I expect to see that the internet and the creation of cyber culture that we see through social media has enhanced many of the defining events for younger generations growing up in some positive ways as well as some negative ways. Thus, growing up only knowing the internet and its purposes has altered the way that our experiences play out as we age, for good and for bad.
ContributorsTomchak, Marissa Janine (Author) / Ingram-Waters, Mary (Thesis director) / Brian, Jennifer (Committee member) / Department of Psychology (Contributor) / School of Politics and Global Studies (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
The purpose of this research is to create a model that will benefit this industry and the many changes to come. As of now, there are limited FTC guidelines which limit the protection of content creators, agencies, and brands. That is when I came up with the idea to develop a model to further improve efficiency of the influencer marketing industry, and to help the entrepreneurs who are leading it. This model provides the framework for a strong start in the influencer marketing industry. Through informational interviews, literary research, field studies, and surveys, the model was developed through the data analysis of each of these tools, based on common themes found within each. This research was conducted from a variety of perspectives, including consumers, brands, agencies, and content creators.
ContributorsFurnas, Madison (Author) / Eaton, John (Thesis director) / Ingram-Waters, Mary (Committee member) / Svirskis, Anthony (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / Watts College of Public Service & Community Solut (Contributor) / Department of Marketing (Contributor) / Dean, W.P. Carey School of Business (Contributor)
Created2022-05
Description
The purpose of this research is to create a model that will benefit this industry and the many changes to come. As of now, there are limited FTC guidelines which limit the protection of content creators, agencies, and brands. That is when I came up with the idea to develop a model to further improve efficiency of the influencer marketing industry, and to help the entrepreneurs who are leading it. This model provides the framework for a strong start in the influencer marketing industry. Through informational interviews, literary research, field studies, and surveys, the model was developed through the data analysis of each of these tools, based on common themes found within each. This research was conducted from a variety of perspectives, including consumers, brands, agencies, and content creators.
ContributorsFurnas, Madison (Author) / Eaton, John (Thesis director) / Ingram-Waters, Mary (Committee member) / Svirskis, Anthony (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor)
Created2022-05
Description
The purpose of this research is to create a model that will benefit this industry and the many changes to come. As of now, there are limited FTC guidelines which limit the protection of content creators, agencies, and brands. That is when I came up with the idea to develop a model to further improve efficiency of the influencer marketing industry, and to help the entrepreneurs who are leading it. This model provides the framework for a strong start in the influencer marketing industry. Through informational interviews, literary research, field studies, and surveys, the model was developed through the data analysis of each of these tools, based on common themes found within each. This research was conducted from a variety of perspectives, including consumers, brands, agencies, and content creators.
ContributorsFurnas, Madison (Author) / Eaton, John (Thesis director) / Ingram-Waters, Mary (Committee member) / Svirskis, Anthony (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor)
Created2022-05