Matching Items (30)
Filtering by
- All Subjects: Social Media
- All Subjects: data
- Creators: Department of Information Systems
- Resource Type: Text
- Status: Published
Description
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
Description
Sagebrush Coffee is a small business in Chandler, Arizona that purchases green beans, roasts them in small batches for quality, and ships fresh, gourmet roasted coffee beans across the nation. Deciding which coffee beans to buy and roast is one of the most crucial business decisions Sagebrush and other gourmet coffee roasters face. Further complicating this decision is the fact that coffee is a crop, and like all crops, has a specific growing season and the exact same product cannot usually be ordered from year to year, even if it proves to be successful. The goal of this research is to use data analytics and visualization to help Sagebrush make better purchasing decisions by identifying consumer purchasing trends and providing a recommendation for their portfolio mix. In the end, I found that Latin American coffees are popular with both returning and first-time customers, but a specific country of origin does not appear to be associated with the top coffee producing countries. Additionally, December is a critical month for Sagebrush and Sagebrush should make sure to target the states with the most sales: California, Pennsylvania, and New York. Arizona has growth potential as it is not one of the top three locations, despite the presence of a physical store. Also included in the following report is a portfolio recommendation suggesting how many of each product based on region, processing type, and roast level to carry in inventory.
ContributorsBlue, Jessica Morgan (Author) / Kellso, James (Thesis director) / Davila, Eddie (Committee member) / Department of Information Systems (Contributor) / Economics Program in CLAS (Contributor) / Department of Supply Chain Management (Contributor) / Morrison School of Agribusiness (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This project analyzes the tweets from the 2016 US Presidential Candidates' personal Twitter accounts. The goal is to define distinct patterns and differences between candidates and parties use of social media as a platform. The data spans the period of September 2015 to March 2016, which was during the primary races for the Republicans and Democrats. The overall purpose of this project is to contribute to finding new ways of driving value from social media, in particular Twitter.
ContributorsMortimer, Schuyler Kenneth (Author) / Simon, Alan (Thesis director) / Mousavi, Seyedreza (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Data has quickly become a cornerstone of society. Across our daily lives, industry, policy, and more, we are experiencing what can only be called a “data revolution” igniting ferociously. While data is gaining more and more importance, consumers do not fully understand the extent of its use and subsequent capitalization by companies. This paper explores the current climate relating to data security and data privacy. It aims to start a conversation regarding the culture around the sharing and collection of data. We explore aspects of data privacy in four tiers: the current cultural and social perception of data privacy, its relevance in our daily lives, its importance in society’s dialogue. Next, we look at current policy and legislature in place today, focusing primarily on Europe’s established GDPR and the incoming California Consumer Privacy Act, to see what measures are already in place and what measures need to be adopted to mold more of a culture of transparency. Next, we analyze current data privacy regulations and power of regulators like the FTC and SEC to see what tools they have at their disposal to ensure accountability in the tech industry when it comes to how our data is used. Lastly, we look at the potential act of treating and viewing data as an asset, and the implications of doing so in the scope of possible valuation and depreciation techniques. The goal of this paper is to outline initial steps to better understand and regulate data privacy and collection practices. Our goal is to bring this issue to the forefront of conversation in society, so that we may start the first step in the metaphorical marathon of data privacy, with the goal of establishing better data privacy controls and become a more data-conscious society.
ContributorsAnderson, Thomas C (Co-author) / Shafeeva, Zarina (Co-author) / Swiech, Jakub (Co-author) / Marchant, Gary (Thesis director) / Sopha, Matthew (Committee member) / WPC Graduate Programs (Contributor) / Department of Finance (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
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.
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
Description
Autonomous vehicles (AV) are capable of producing massive amounts of real time and precise data. This data has the ability to present new business possibilities across a vast amount of markets. These possibilities range from simple applications to unprecedented use cases. With this in mind, the three main objectives we sought to accomplish in our thesis were to: 1. Understand if there is monetization potential in autonomous vehicle data 2. Create a financial model of what detailing the viability of AV data monetization 3. Discover how a particular company (Company X) can take advantage of this opportunity, and outline how that company might access this autonomous vehicle data.
ContributorsCarlton, Corrine (Co-author) / Clark, Rachael (Co-author) / Quintana, Alex (Co-author) / Shapiro, Brandon (Co-author) / Sigrist, Austin (Co-author) / Simonson, Mark (Thesis director) / Reber, Kevin (Committee member) / School of Accountancy (Contributor) / Department of Finance (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This case study analyzed the internal controls of a real estate company using the widely accepted COSO framework. Testing of the internal environment and controls was completed using the COSO framework. The major internal control problem identified in the study was a lack of ethical standards in the control environment. In addition to this main problem, inadequate documentation, no separation of duties, and unqualified employees were also identified as violations of effective internal controls. The department of real estate ordered a "cease and desist" on August 8, 2013 due to illegal company activities. The company participated in illegal actions regarding: the trust account and company documentation and procedures. Material weaknesses were found in the company's internal controls; therefore the result of this study was an adverse opinion on internal controls.
ContributorsFrederick, Nicole Lorraine (Author) / Munshi, Perseus (Thesis director) / Benali, Kayla (Committee member) / Barrett, The Honors College (Contributor) / School of Accountancy (Contributor) / Department of Psychology (Contributor)
Created2013-12
Description
The goal of this thesis is to conduct a descriptive analysis of the gross domestic product (GDP) sector composition of countries around the world and their respective levels of economic development with consideration of their geographic locations, economic growth over time, and their economic sizes. This analysis will be centered around exploring the differences of the GDP composition of countries at different levels of development, testing the consensus that developed countries tend to be focused on the services sector in comparison to less developed ones, who trend towards focus on the agricultural one. These findings will be primarily attained through use of data interpretation and regression analysis utilizing the statistical software packages of Stata and Excel. Results and analysis are to be supported by powerful data visualizations created in Tableau and the careful examination of said visualizations.
Due to the sheer amount of macro-economic factors and the case specific incidences involved in the determination of a country’s level of economic development, this thesis will focus entirely on the descriptive analysis of the relationship between a country’s GDP sector composition within the agricultural, industrial, and services sectors and their level of economic development measured in GDP per capita. This study will explore the relationship between GDP per capita and geographic regions, growth over time, and economic size as well. These relationships will be used to determine if said factors need to be controlled for when analyzing the relationship between a country’s sector composition and its level of development. A better understanding of what countries look like at all levels of development helps build a complete picture of a what makes a country successful and could be used in future studies that seek to predict economic success based on more and/or separate variables.
Due to the sheer amount of macro-economic factors and the case specific incidences involved in the determination of a country’s level of economic development, this thesis will focus entirely on the descriptive analysis of the relationship between a country’s GDP sector composition within the agricultural, industrial, and services sectors and their level of economic development measured in GDP per capita. This study will explore the relationship between GDP per capita and geographic regions, growth over time, and economic size as well. These relationships will be used to determine if said factors need to be controlled for when analyzing the relationship between a country’s sector composition and its level of development. A better understanding of what countries look like at all levels of development helps build a complete picture of a what makes a country successful and could be used in future studies that seek to predict economic success based on more and/or separate variables.
ContributorsStojsin, Rastko (Author) / Goegan, Brian (Thesis director) / Lopez, Andres Diaz (Committee member) / Department of Economics (Contributor) / Department of Information Systems (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Cognitive technology has been at the forefront of the minds of many technology, government, and business leaders, because of its potential to completely revolutionize their fields. Furthermore, individuals in financial statement auditor roles are especially focused on the impact of cognitive technology because of its potential to eliminate many of the tedious, repetitive tasks involved in their profession. Adopting new technologies that can autonomously collect more data from a broader range of sources, turn the data into business intelligence, and even make decisions based on that data begs the question of whether human roles in accounting will be completely replaced. A partial answer: If the ramifications of past technological advances are any indicator, cognitive technology will replace some human audit operations and grow some new and higher order roles for humans. It will shift the focus of accounting professionals to more complex judgment and analysis.
The next question: What do these changes in the roles and responsibilities look like for the auditors of the future? Cognitive technology will assuredly present new issues for which humans will have to find solutions.
• How will humans be able to test the accuracy and completeness of the decisions derived by cognitive systems?
• If cognitive computing systems rely on supervised learning, what is the most effective way to train systems?
• How will cognitive computing fair in an industry that experiences ever-changing industry regulations?
• Will cognitive technology enhance the quality of audits?
In order to answer these questions and many more, I plan on examining how cognitive technologies evolved into their use today. Based on this historic trajectory, stakeholder interviews, and industry research, I will forecast what auditing jobs may look like in the near future taking into account rapid advances in cognitive computing.
The conclusions forecast a future in auditing that is much more accurate, timely, and pleasant. Cognitive technologies allow auditors to test entire populations of transactions, to tackle audit issues on a more continuous basis, to alleviate the overload of work that occurs after fiscal year-end, and to focus on client interaction.
The next question: What do these changes in the roles and responsibilities look like for the auditors of the future? Cognitive technology will assuredly present new issues for which humans will have to find solutions.
• How will humans be able to test the accuracy and completeness of the decisions derived by cognitive systems?
• If cognitive computing systems rely on supervised learning, what is the most effective way to train systems?
• How will cognitive computing fair in an industry that experiences ever-changing industry regulations?
• Will cognitive technology enhance the quality of audits?
In order to answer these questions and many more, I plan on examining how cognitive technologies evolved into their use today. Based on this historic trajectory, stakeholder interviews, and industry research, I will forecast what auditing jobs may look like in the near future taking into account rapid advances in cognitive computing.
The conclusions forecast a future in auditing that is much more accurate, timely, and pleasant. Cognitive technologies allow auditors to test entire populations of transactions, to tackle audit issues on a more continuous basis, to alleviate the overload of work that occurs after fiscal year-end, and to focus on client interaction.
ContributorsWitkop, David (Author) / Dawson, Gregory (Thesis director) / Munshi, Perseus (Committee member) / School of Accountancy (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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 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