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This paper looks at the growth of influencer marketing in application and how it has shifted the relationship between brands and consumers. Barriers to enter the space and methods of practice are discussed and analyzed to project the accessibility of obtaining influencer status. Best practices for brands and influencers are

This paper looks at the growth of influencer marketing in application and how it has shifted the relationship between brands and consumers. Barriers to enter the space and methods of practice are discussed and analyzed to project the accessibility of obtaining influencer status. Best practices for brands and influencers are outlined based on research, and key findings are analyzed from interviewed participants that play an active role in the field. Another component of the paper includes the discussion of the significance of platform dependence regarding influencers and brands using social media channels to reach consumers. The dynamic of the relationship that exists between consumers, brands and platforms is demonstrated through a model to demonstrate the interdependence of the relationship. The final component of the paper involves the exploration of the field as an active participant through an experiment that was conducted by the researcher on behalf of the question: can anyone be an influencer? The answer to this question is explored through personal accounts on the journey during an eight month process of testing content creation and promotion to build awareness and increase engagement. The barriers to enter the space as an influencer and to collaborate with brands is addressed through the process of testing tactics and strategies on social channels, along with travel expeditions across Arizona to contribute to content creation purposed into blog articles. The findings throughout the paper are conclusive that the value of influencer marketing is increasing as more brands validate and utilize this method in their marketing efforts.
ContributorsDavis, Natalie Marie (Author) / Giles, Bret (Thesis director) / Schlacter, John (Committee member) / Department of Information Systems (Contributor) / Department of Marketing (Contributor) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Cryptocurrencies are notorious for its volatility. But with its incredible rise in price, Bitcoin keep being on the top among the trending topics on social media. Although doubts continue to rise with price, Bloomberg even make critics on Bitcoin as ‘the biggest bubble in the history’, some investors still hold

Cryptocurrencies are notorious for its volatility. But with its incredible rise in price, Bitcoin keep being on the top among the trending topics on social media. Although doubts continue to rise with price, Bloomberg even make critics on Bitcoin as ‘the biggest bubble in the history’, some investors still hold strong enthusiasm and confidence towards Bitcoin. As contradicting opinions increase, it is worthy to dive into discussions on social media and use a scientific method to evaluate public’s non-negligible role in crypto price fluctuation.

Sentiment analysis, which is a notably method in text mining, can be used to extract the sentiment from people’s opinion. It then provides us with valuable perception on a topic from the public’s attitude, which create more opportunities for deeper analysis and prediction.

The thesis aims to investigate public’s sentiment towards Bitcoin through analyzing 10 million Bitcoin related tweets and assigning sentiment points on tweets, then using sentiment fluctuation as a factor to predict future crypto fluctuation. Price prediction is achieved by using a machine learning model called Recurrent Neural Network which automatically learns the pattern and generate following results with memory. The analysis revels slight connection between sentiment and crypto currency and the Neural Network model showed a strong connection between sentiment score and future price prediction.
ContributorsZhu, Xiaoyu (Author) / Benjamin, Victor (Thesis director) / Qinglai, He (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
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The United States is in a period of political turmoil and polarization. New technologies have matured over the last ten years, which have transformed an individual’s relationship with society and government. The emergence of these technologies has revolutionized access to both information and misinformation. Skills such as bias recognition and

The United States is in a period of political turmoil and polarization. New technologies have matured over the last ten years, which have transformed an individual’s relationship with society and government. The emergence of these technologies has revolutionized access to both information and misinformation. Skills such as bias recognition and critical thinking are more imperative than in any other time to separate truth from false or misleading information. Meanwhile, education has not evolved with these changes. The average individual is more likely to come to uninformed conclusions and less likely to listen to differing perspectives. Moreover, technology is further complicating and compounding other issues in the political process. All of this is manifesting in division among the American people who elect more polarized politicians who increasingly fail to find avenues for compromise.

In an effort to address these trends, we founded a student organization, The Political Literates, to fight political apathy by delivering political news in an easy to understand and unbiased manner. Inspired by our experience with this organization, we combine our insights with research to paint a new perspective on the state of the American political system.

This thesis analyzes various issues identified through our observations and research, with a heavy emphasis on using examples from the 2016 election. Our focus is how new technologies like data analytics, the Internet, smartphones, and social media are changing politics by driving political and social transformation. We identify and analyze five core issues that have been amplified by new technology, hindering the effectiveness of elections and further increasing political polarization:

● Gerrymandering which skews partisan debate by forcing politicians to pander to ideologically skewed districts.
● Consolidation of media companies which affects the diversity of how news is shared.
● Repeal of the Fairness Doctrine which allowed media to become more partisan.
● The Citizens United Ruling which skews power away from average voters in elections.
● A Failing Education System which does not prepare Americans to be civically engaged and to avoid being swayed by biased or untrue media.

Based on our experiment with the Political Literates and our research, we call for improving how critical thinking and civics is taught in the American education system. Critical thought and civics must be developed pervasively. With this, more people would be able to form more sophisticated views by listening to others to learn rather than win, listening less to irrelevant information, and forming a culture with more engagement in politics. Through this re-enlightenment, many of America’s other problems may evaporate or become more actionable.
ContributorsStenseth, Kyle (Co-author) / Tumas, Trevor (Co-author) / Mokwa, Michael (Thesis director) / Eaton, John (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Sandra Day O'Connor College of Law (Contributor) / Watts College of Public Service & Community Solut (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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This thesis studies the area of sentiment analysis and its general uses, benefits, and limitations. Social networking, blogging, and online forums have turned the Web into a vast repository of comments on many topics. Sentiment analysis is the process of using software to analyze social media to gauge the attitudes

This thesis studies the area of sentiment analysis and its general uses, benefits, and limitations. Social networking, blogging, and online forums have turned the Web into a vast repository of comments on many topics. Sentiment analysis is the process of using software to analyze social media to gauge the attitudes or sentiments of the users/authors concerning a particular subject. Sentiment analysis works by processing (data mining) unstructured textual evidence using natural language processing and machine learning to determine a positive, negative, or neutral measurement. When utilized correctly, sentiment analysis has the potential to glean valuable insights into consumers' minds, which in turn leads to increased revenue and improved customer satisfaction for businesses. This paper looks at four industries in which sentiment analysis is being used or being considered: retail/services, politics, healthcare, and finances. The goal of the thesis will be to explore whether sentiment analysis has been used successfully for economic or social benefit and whether it is a practical solution for analyzing consumer opinion.
ContributorsSoumya, Saswati (Author) / Uday, Kulkarni (Thesis director) / Brooks, Daniel (Committee member) / Barrett, The Honors College (Contributor) / Department of Economics (Contributor) / WPC Graduate Programs (Contributor) / Department of Information Systems (Contributor)
Created2014-05
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Description
The prevalence of bots, or automated accounts, on social media is a well-known problem. Some of the ways bots harm social media users include, but are not limited to, spreading misinformation, influencing topic discussions, and dispersing harmful links. Bots have affected the field of disaster relief on social media as

The prevalence of bots, or automated accounts, on social media is a well-known problem. Some of the ways bots harm social media users include, but are not limited to, spreading misinformation, influencing topic discussions, and dispersing harmful links. Bots have affected the field of disaster relief on social media as well. These bots cause problems such as preventing rescuers from determining credible calls for help, spreading fake news and other malicious content, and generating large amounts of content which burdens rescuers attempting to provide aid in the aftermath of disasters. To address these problems, this research seeks to detect bots participating in disaster event related discussions and increase the recall, or number of bots removed from the network, of Twitter bot detection methods. The removal of these bots will also prevent human users from accidentally interacting with these bot accounts and being manipulated by them. To accomplish this goal, an existing bot detection classification algorithm known as BoostOR was employed. BoostOR is an ensemble learning algorithm originally modeled to increase bot detection recall in a dataset and it has the possibility to solve the social media bot dilemma where there may be several different types of bots in the data. BoostOR was first introduced as an adjustment to existing ensemble classifiers to increase recall. However, after testing the BoostOR algorithm on unobserved datasets, results showed that BoostOR does not perform as expected. This study attempts to improve the BoostOR algorithm by comparing it with a baseline classification algorithm, AdaBoost, and then discussing the intentional differences between the two. Additionally, this study presents the main factors which contribute to the shortcomings of the BoostOR algorithm and proposes a solution to improve it. These recommendations should ensure that the BoostOR algorithm can be applied to new and unobserved datasets in the future.
ContributorsDavis, Matthew William (Author) / Liu, Huan (Thesis director) / Nazer, Tahora H. (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
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The consumer decision making process is becoming less complicated, as consumers are turning more and more to social media and peers for reviews and suggestions of new products to purchase. Changes in purchasing trends, along with other external factors, have created a perfect environment for influencer marketing to become more

The consumer decision making process is becoming less complicated, as consumers are turning more and more to social media and peers for reviews and suggestions of new products to purchase. Changes in purchasing trends, along with other external factors, have created a perfect environment for influencer marketing to become more effective for brands than traditional marketing strategies (including television, print, email and radio advertising)—by reaching the right target market with easier ways to track conversion rates and other returns on investment. This thesis looks at the factors that go in to influencer marketing, including why brands utilize this strategy—in terms of budget, returns on investment and best practices for finding the perfect influencers. It also looks at influencer marketing from the view of the influencers themselves. This thesis looks at the spectrum of influence and the motivation and goals of each level—from macro-influencers to micro-influencers and brand advocates. To better understand the research presented in this thesis, a case study of a successful brand, analysis of influencers and a creative project are all presented.
ContributorsOakes, Katherine Danielle (Author) / Montoya, Detra (Thesis director) / Giles, Bret (Committee member) / Department of Supply Chain Management (Contributor) / Department of Marketing (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The concept of branding has been around for centuries, but personal branding is a relatively new concept that has been defined and executed by many public figures. With the rise of technological advancements like social media, professional athletes have ample opportunities to connect with consumers outside of their respective court.

The concept of branding has been around for centuries, but personal branding is a relatively new concept that has been defined and executed by many public figures. With the rise of technological advancements like social media, professional athletes have ample opportunities to connect with consumers outside of their respective court. Our thesis team conducted research with Dr. John Eaton and Professor Daniel McIntosh to analyze how athletes’ actions and behaviors affect consumers’ opinions about their brand.
We developed multiple surveys that were distributed to Marketing & Business Performance (MKT 300) students at Arizona State University and AWS Mechanical Turk Workers. The goal of obtaining information from both college students and paid survey-takers was to compile a diverse set of opinions regarding how consumers react to athletes’ social media and public behavior. This led us to analyze how consumers interact with athletes on social media platforms based on the sport they play and consequences of their actions. After examining our consumer research, interviewing executives in the legal background, and talking to some of the university’s top-prospective athletes to gain different viewpoints, we created consumer and athlete categories.
We established six main consumer categories and six main athlete social media strategy personas in order to create social media strategy recommendations. With this information, athletes have the opportunity to develop well-thought out social media strategies that are more tailored to their fan base(s). Athletes must be cognizant of how the content on their social media accounts and their public actions will affect consumers’ perceptions about who they are and their personal brand.
ContributorsRishwain, Demetra Nicole (Co-author) / Delgado, Samantha (Co-author) / Sminkey, Marie (Co-author) / Eaton, John (Thesis director) / McIntosh, Daniel (Committee member) / Department of Marketing (Contributor, Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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The purpose of this thesis was to develop a tool to provide information and data for design teams to use throughout the mobile application design process. Ideally, this would enable teams to see patterns in iterative design, and ultimately use data-driven analysis to make their own decisions. The initial problem

The purpose of this thesis was to develop a tool to provide information and data for design teams to use throughout the mobile application design process. Ideally, this would enable teams to see patterns in iterative design, and ultimately use data-driven analysis to make their own decisions. The initial problem was a lack of available information offered by mobile application design teams—the initial goal being to work closely with design teams to learn their decision-making methodology. However, every team that was reached out to responded with rejection, presenting a new problem: a lack of access to quality information regarding the decision-making process for mobile applications. This problem was addressed by the development of an ethical hacking script that retrieves reviews in bulk from the Google Play Store using Python. The project was a success—by feeding an application’s unique Play Store ID, the script retrieves a user-specified amount of reviews (up to millions) for that mobile application and the 4 “recommended” applications from the Play Store. Ultimately, this thesis proved that protected reviews on the Play Store can be ethically retrieved and used for data-driven decision making and identifying patterns in an application’s iterative design. This script provides an automated tool for teams to “put a finger on the pulse” of their target applications.
ContributorsDyer, Mitchell Patrick (Author) / Lin, Elva (Thesis director) / Giles, Charles (Committee member) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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Social media has become a direct and effective means of transmitting personal opinions into the cyberspace. The use of certain key-words and their connotations in tweets portray a meaning that goes beyond the screen and affects behavior. During terror attacks or worldwide crises, people turn to social media as a

Social media has become a direct and effective means of transmitting personal opinions into the cyberspace. The use of certain key-words and their connotations in tweets portray a meaning that goes beyond the screen and affects behavior. During terror attacks or worldwide crises, people turn to social media as a means of managing their anxiety, a mechanism of Terror Management Theory (TMT). These opinions have distinct impacts on the emotions that people express both online and offline through both positive and negative sentiments. This paper focuses on using sentiment analysis on twitter hash-tags during five major terrorist attacks that created a significant response on social media, which collectively show the effects that 140-character tweets have on perceptions in social media. The purpose of analyzing the sentiments of tweets after terror attacks allows for the visualization of the effect of key-words and the possibility of manipulation by the use of emotional contagion. Through sentiment analysis, positive, negative and neutral emotions were portrayed in the tweets. The keywords detected also portray characteristics about terror attacks which would allow for future analysis and predictions in regards to propagating a specific emotion on social media during future crisis.
ContributorsHarikumar, Swathikrishna (Author) / Davulcu, Hasan (Thesis director) / Bodford, Jessica (Committee member) / Computer Science and Engineering Program (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description

As social media and technology continue to impact the way students communicate and receive information, it is encouraged that university student-run organizations utilize social media platforms as a tool to further the development of their organizations. Social media platforms allow student organizations to network, promote awareness of their organizations, current

As social media and technology continue to impact the way students communicate and receive information, it is encouraged that university student-run organizations utilize social media platforms as a tool to further the development of their organizations. Social media platforms allow student organizations to network, promote awareness of their organizations, current campus events, and provide the opportunity to develop strong associations and interactions among students. Overall, student-run organizations currently utilize a wide variety of social media; however, frequently it is used without a clear understanding of its role and best practices, which could lead to a loss of effectiveness in their communication with students. Therefore, these factors suggest the need for university student-run organizations to recognize and understand the opportunities that effective social media strategies can bring as a communication tool to enhance student engagement.

ContributorsBastien, Kimberly L (Author) / Byrne, Jared (Thesis director) / LaRoche, Catherine-Ann (Committee member) / Walter Cronkite School of Journalism and Mass Comm (Contributor) / Department of Marketing (Contributor) / WPC Graduate Programs (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05