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President Donald Trump announced his candidacy in June 2015, and the America immediately knew that he was an unorthodox candidate. Early on in his campaign, Trump isolated groups of people and treated them as enemies, but none so consistently as the news media. What began as criticism of "fake news,"

President Donald Trump announced his candidacy in June 2015, and the America immediately knew that he was an unorthodox candidate. Early on in his campaign, Trump isolated groups of people and treated them as enemies, but none so consistently as the news media. What began as criticism of "fake news," turned into calling the news media "the opposition party." However, media professionals agree that when the Trump administration called the news media the "enemy of the American people" \u2014 a line had been crossed. In the last two years Trump has denied simple fact and credible journalism countless times. His avid use of social media allows his messages to reach millions of people in moments - which had the potential to be a positive thing. However, Twitter is often where Trump turns to dispute the media, science, fact or anything else that "opposes" him. If Americans cannot believe the news media, cannot believe science, and cannot believe established fact, what can they believe? Allowing one man, in this case, Trump, to become the beacon of truth is dangerous and destructive to democracy. The news media must do their best to recapture the trust and faith of the American people by producing good, honest journalism. Seasoned journalism professionals say that his attacks on the media are likely a facade, just another way to appeal to his base, but that those attacks have the potential to wreak havoc in American society. Regardless of Trump's intentions, the toxicity between him and news media could have consequences that reach far beyond his presidency.
Created2017-12
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This paper presents the design and evaluation of a haptic interface for augmenting human-human interpersonal interactions by delivering facial expressions of an interaction partner to an individual who is blind using a visual-to-tactile mapping of facial action units and emotions. Pancake shaftless vibration motors are mounted on the back of

This paper presents the design and evaluation of a haptic interface for augmenting human-human interpersonal interactions by delivering facial expressions of an interaction partner to an individual who is blind using a visual-to-tactile mapping of facial action units and emotions. Pancake shaftless vibration motors are mounted on the back of a chair to provide vibrotactile stimulation in the context of a dyadic (one-on-one) interaction across a table. This work explores the design of spatiotemporal vibration patterns that can be used to convey the basic building blocks of facial movements according to the Facial Action Unit Coding System. A behavioral study was conducted to explore the factors that influence the naturalness of conveying affect using vibrotactile cues.
ContributorsBala, Shantanu (Author) / Panchanathan, Sethuraman (Thesis director) / McDaniel, Troy (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / Department of Psychology (Contributor)
Created2014-05
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Bots tamper with social media networks by artificially inflating the popularity of certain topics. In this paper, we define what a bot is, we detail different motivations for bots, we describe previous work in bot detection and observation, and then we perform bot detection of our own. For our bot

Bots tamper with social media networks by artificially inflating the popularity of certain topics. In this paper, we define what a bot is, we detail different motivations for bots, we describe previous work in bot detection and observation, and then we perform bot detection of our own. For our bot detection, we are interested in bots on Twitter that tweet Arabic extremist-like phrases. A testing dataset is collected using the honeypot method, and five different heuristics are measured for their effectiveness in detecting bots. The model underperformed, but we have laid the ground-work for a vastly untapped focus on bot detection: extremist ideal diffusion through bots.
ContributorsKarlsrud, Mark C. (Author) / Liu, Huan (Thesis director) / Morstatter, Fred (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
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This study examined the brand personality types and social media practices of six college athletic Twitter accounts. Specifically, this study investigated whether certain brand personalities corresponded with specific social media practices on Twitter. The author conducted a content analysis of each school's tweets to measure brand personality and scraped data

This study examined the brand personality types and social media practices of six college athletic Twitter accounts. Specifically, this study investigated whether certain brand personalities corresponded with specific social media practices on Twitter. The author conducted a content analysis of each school's tweets to measure brand personality and scraped data in order to collect social media practice information. Results suggest that brand personality and social media practices are distinct. Extraversion was the most common personality type among all schools. In addition, schools that tweeted less frequently than others exhibited more brand personality and used more visual media.
ContributorsDave, Simran Sangita (Author) / Gilpin, Dawn (Thesis director) / Reed, Sada (Committee member) / Pucci, Jessica (Committee member) / School of Life Sciences (Contributor) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
Social media is changing the way journalists operate; their use of Twitter is potentially representational of that change. Because of Twitter, journalists can connect to stories, sources, and audiences in ways they never could before. Because this is an evolving practice, role models can be difficult to find, which presents

Social media is changing the way journalists operate; their use of Twitter is potentially representational of that change. Because of Twitter, journalists can connect to stories, sources, and audiences in ways they never could before. Because this is an evolving practice, role models can be difficult to find, which presents a problem for journalism students. In broadcast journalism, the challenge is even more pronounced when it comes to finding women exemplars for female students; female students are more likely to relate to female role models.This study, using in-depth interviews and textual analysis, examines how Twitter is being used by four prominent journalists in one competitive market. The Twitter feeds of four female TV news anchors in Phoenix, Arizona, the 12th largest broadcast market in the United States, are explored in terms of content and practice. The results show that they used Twitter daily and for more than just tweeting out the day's news, suggesting that Twitter has become a standard journalistic tool and a practice worth emulating.
ContributorsMolina, Tara Lea (Author) / Lodato, Mark (Thesis director) / Thornton, Leslie (Committee member) / Barrett, The Honors College (Contributor) / Walter Cronkite School of Journalism and Mass Communication (Contributor)
Created2014-05
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Twitter has become a very popular social media site that is used daily by many people and organizations. This paper will focus on the financial aspect of Twitter, as a process will be shown to be able to mine data about specific companies' stock prices. This was done by writing

Twitter has become a very popular social media site that is used daily by many people and organizations. This paper will focus on the financial aspect of Twitter, as a process will be shown to be able to mine data about specific companies' stock prices. This was done by writing a program to grab tweets about the stocks of the thirty companies in the Dow Jones.
ContributorsLarson, Grant Elliott (Author) / Davulcu, Hasan (Thesis director) / Ye, Jieping (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2014-05
Description
This thesis documentary film takes a look at the dysfunctional but ongoing relationship between Twitter and sports journalism. The foundation of this relationship's dysfunction is what I have coined as the Twitter Outrage Cycle. In this cycle a sports broadcasting personality comments on a matter while on-air. Next, the program's

This thesis documentary film takes a look at the dysfunctional but ongoing relationship between Twitter and sports journalism. The foundation of this relationship's dysfunction is what I have coined as the Twitter Outrage Cycle. In this cycle a sports broadcasting personality comments on a matter while on-air. Next, the program's audience where the comments were spoken becomes offended by the statement. After that, the offended audience members express their outrage on social media, most namely Twitter. Finally the cycle culminates with the public outrage pressuring networks and its executives to either suspended or fire the individual that said the controversial statements. This cycle began to occur on a more consistent basis starting in 2012. It became such a regular occurrence that many on-air talent figures have noticed and taken precautionary measures to either avoid or confront the Outrage Cycles. This documentary uses the voice of seven figures within the sports media and online interaction forum. Notable using the voices of three notable individuals that currently have a prominent voice in sports journalism. As well as a neutral social media curator who clearly explains the psyche behind these outraged viewer's mindsets. Through these four main voices their ideals and opinions on the matter weave together, disagree with each other at times but ultimately help the viewer come to an understanding of why these Outrage Cycles occur and what needs to be done in order for them to cease. We Should Talk: The Relationship Between Twitter and Sports Journalism is a documentary film that looks to illustrate a seemingly minimal part of many people's lives that when taken into perspective many people look at in a very serious light.
ContributorsNeely, Cammeron Allen Douglas (Author) / Kurland, Brett (Thesis director) / Fergus, Tom (Committee member) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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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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In the past ten years, social network services have expanded from a digital method in which the public connects with only their friends and families. Social network services have evolved to a highly-accessible, convenient, cost-effective tool to engage with communities beyond one's frequented social circle on a local, national, and

In the past ten years, social network services have expanded from a digital method in which the public connects with only their friends and families. Social network services have evolved to a highly-accessible, convenient, cost-effective tool to engage with communities beyond one's frequented social circle on a local, national, and global scale. Many politicians have adapted in order to use social network services to connect directly with their constituents. Politicians have begun to use their profiles on social network services as their own privately owned publicity channel, publishing raw "material" like political opinions or legal advocacy, appearances at events and media like photos, videos or links to maintain transparency and accessibility to their constituencies. The content analysis investigates the use of a social network service (Twitter) by five different Arizonan politicians from different municipal, state and federal offices over the period of six months. All posts on Twitter were recorded, evaluated, and categorized by content into one of seventeen different divisions: Constituent Connection, Correction, Culture, Economy, Education, Environment, Healthcare, Humanitarianism, International, Military, Operational, Personal, Political Activity, Reply to Constituent, Security, Social Issues or Sports. The date, category, content, media type and engagement (replies, retweets, and favorites) were also recorded. Understanding how political figures connect and engage with their constituencies contributes to understanding modern campaigning and modern government; politicians are now finding it imperative to have and maintain a social media presence in order to gain relevance, transparency and accessibility with their constituencies. This study examines how politicians are currently utilizing these micro-blogging sites.
Created2018-05
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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