Matching Items (265)
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- All Subjects: Social Media
- Creators: Barrett, The Honors College
- Resource Type: Text
- Status: Published
Description
The objective of this research is to determine an approach for automating the learning of the initial lexicon used in translating natural language sentences to their formal knowledge representations based on lambda-calculus expressions. Using a universal knowledge representation and its associated parser, this research attempts to use word alignment techniques to align natural language sentences to the linearized parses of their associated knowledge representations in order to learn the meanings of individual words. The work includes proposing and analyzing an approach that can be used to learn some of the initial lexicon.
ContributorsBaldwin, Amy Lynn (Author) / Baral, Chitta (Thesis director) / Vo, Nguyen (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
The selfie craze has taken over smartphone users. Despite a wealth of published opinion pieces on the matter, there lacks a constructive and academically-based dialogue about selfies. "Presentation of Selfie" is a creative, interactive space that analyzes a sample of collected selfies. The project takes a look at how age, relationships and identities play a role in the social significance of selfie culture.
ContributorsJeffords, Alison Rae (Author) / McGibbney-Vlahoulis, Michelle (Thesis director) / Leong, Karen (Committee member) / Barrett, The Honors College (Contributor) / School of Social Transformation (Contributor) / Department of Marketing (Contributor)
Created2015-05
Description
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
Description
This project explores the history of technology and social media, and their impact on the music industry. Social media and music culture are part of a remix culture, which encompasses new ways of recreating old content. Social media is not a new phenomenon, but has existed for centuries in various forms, dating back to ancient cultures. Music is constantly changing due to the remix culture- each new music style is created by changing what exists to fit the individual musician's style. Technological advances pushed the music industry to change, from the start to audio recording, to the digital sharing that is present in 2015, creating the musical culture as we presently know it. Due to the way that social media and music are interacting, a new platform is necessary to serve the artists in the music industry. Marketing on social media is incredibly powerful, but is ill-suited for small artists. As a result, SoundScope was developed to serve the needs of small musicians on social media. Soundscope develops a website that lets musicians use social media to it's greatest capacity and take advantage of the remix culture and the concept of virality that has developed with online communication. It uses a voting/ranking system to populate and organize it's home page, allowing listeners to find the most popular music first, and artists can get feedback based on the voting system and commenting capability. These create the community necessary for effective marketing and sharing of garage artist's music in the digital sphere.
ContributorsCash, Aimee Nicole (Author) / Silcock, Bill (Thesis director) / Dodge, Nancie (Committee member) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
This paper presents work that was done to create a system capable of facial expression recognition (FER) using deep convolutional neural networks (CNNs) and test multiple configurations and methods. CNNs are able to extract powerful information about an image using multiple layers of generic feature detectors. The extracted information can be used to understand the image better through recognizing different features present within the image. Deep CNNs, however, require training sets that can be larger than a million pictures in order to fine tune their feature detectors. For the case of facial expression datasets, none of these large datasets are available. Due to this limited availability of data required to train a new CNN, the idea of using naïve domain adaptation is explored. Instead of creating and using a new CNN trained specifically to extract features related to FER, a previously trained CNN originally trained for another computer vision task is used. Work for this research involved creating a system that can run a CNN, can extract feature vectors from the CNN, and can classify these extracted features. Once this system was built, different aspects of the system were tested and tuned. These aspects include the pre-trained CNN that was used, the layer from which features were extracted, normalization used on input images, and training data for the classifier. Once properly tuned, the created system returned results more accurate than previous attempts on facial expression recognition. Based on these positive results, naïve domain adaptation is shown to successfully leverage advantages of deep CNNs for facial expression recognition.
ContributorsEusebio, Jose Miguel Ang (Author) / Panchanathan, Sethuraman (Thesis director) / McDaniel, Troy (Committee member) / Venkateswara, Hemanth (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Many programmable matter systems have been proposed and realized recently, each often tailored toward a particular task or physical setting. In our work on self-organizing particle systems, we abstract away from specific settings and instead describe programmable matter as a collection of simple computational elements (to be referred to as particles) with limited computational power that each perform fully distributed, local, asynchronous algorithms to solve system-wide problems of movement, configuration, and coordination. In this thesis, we focus on the compression problem, in which the particle system gathers as tightly together as possible, as in a sphere or its equivalent in the presence of some underlying geometry. While there are many ways to formalize what it means for a particle system to be compressed, we address three different notions of compression: (1) local compression, in which each individual particle utilizes local rules to create an overall convex structure containing no holes, (2) hole elimination, in which the particle system seeks to detect and eliminate any holes it contains, and (3) alpha-compression, in which the particle system seeks to shrink its perimeter to be within a constant factor of the minimum possible value. We analyze the behavior of each of these algorithms, examining correctness and convergence where appropriate. In the case of the Markov Chain Algorithm for Compression, we provide improvements to the original bounds for the bias parameter lambda which influences the system to either compress or expand. Lastly, we briefly discuss contributions to the problem of leader election--in which a particle system elects a single leader--since it acts as an important prerequisite for compression algorithms that use a predetermined seed particle.
ContributorsDaymude, Joshua Jungwoo (Author) / Richa, Andrea (Thesis director) / Kierstead, Henry (Committee member) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This study investigates the use and perception of communications efforts among 197 animal-related and human services nonprofit organizations. Several facets of nonprofit communication such as traditional communication usage, social media adoption and usage, and the overall perception of the organizations' communications efforts were examined using a survey and Form 990 analysis. More in-depth analysis was conducted on the participating organizations' Facebook and Twitter accounts as well. After analyzing this data, the study found significant differences in how these two types of nonprofit organizations conduct their communications efforts. Animal-related organizations were much more active and saw higher levels of engagement on Facebook than human services organizations; however, there were no differences in how both types of organizations used Twitter. This study also found that human services organizations are more likely to have full-time or part-time staff members in charge of their communications, while animal-related organizations were more likely to assign this responsibility to a volunteer. These findings contribute valuable insight into how different types of nonprofit organizations are communicating with their stakeholders.
ContributorsColeman, Alexandria Elizabeth (Author) / Wu, Xu (Thesis director) / Taj, Torrie (Committee member) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor) / School of Community Resources and Development (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Instead of providing the illusion of agency to a reader via a tree or network of prewritten, branching paths, an interactive story should treat the reader as a player who has meaningful influence on the story. An interactive story can accomplish this task by giving the player a large toolset for expression in the plot. LudoNarrare, an engine for interactive storytelling, puts "verbs" in this toolset. Verbs are contextual choices of action given to agents in a story that result in narrative events. This paper begins with an analysis and statement of the problem of creating interactive stories. From here, various attempts to solve this problem, ranging from commercial video games to academic research, are given a brief overview to give context to what paths have already been forged. With the background set, the model of interactive storytelling that the research behind LudoNarrare led to is exposed in detail. The section exploring this model contains explanations on what storyworlds are and how they are structured. It then discusses the way these storyworlds can be brought to life. The exposition on the LudoNarrare model finally wraps up by considering the way storyworlds created around this model can be designed. After the concepts of LudoNarrare are explored in the abstract, the story of the engine's research and development and the specifics of its software implementation are given. With LudoNarrare fully explained, the focus then turns to plans for evaluation of its quality in terms of entertainment value, robustness, and performance. To conclude, possible further paths of investigation for LudoNarrare and its model of interactive storytelling are proposed to inspire those who wish to continue in the spirit of the project.
ContributorsStark, Joshua Matthew (Author) / VanLehn, Kurt (Thesis director) / Wetzel, Jon (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
Current popular NBA mobile applications do little to provide information about the NBA's players, usually providing limited statistical information or news and completely ignoring players' presence on social media. For fans, especially fans who are unfamiliar with the NBA, finding this information by themselves can be a daunting task, one which requires extensive knowledge about how the NBA provides media related to its players. NBA PlayerTrack has been designed to centralize player information from a variety of media streams, making it easier for fans to learn about and stay up-to-date with players and enabling fan discussion about those players and the NBA in general. By providing a variety of references to the locations of player information, NBA PlayerTrack also serves as a tool for learning about how and where the NBA presents player-related media, allowing fans to more easily locate information they desire as they become more invested in the NBA.
ContributorsSethia, Sumbhav (Author) / Davulcu, Hasan (Thesis director) / Faucon, Philippe (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
This paper examines the relationship between feminism and social media and evaluates the ability of social media to function as an effective platform for the advancement of feminism's objectives. In the decades before social media became an integral part of culture, the popularity of feminism deteriorated and feminist voices were unsure that it could be revived or popularized again. However, in recent years, women have used social media as a mechanism to communicate and disseminate feminist ideas. The birth of what is called "hashtag feminism" has been a fundamental shift in the way feminism is done and advocated for in modern culture. In light of this dramatic shift in venue for feminist conversations, academic feminists are asking a series of pertinent questions: Is social media good for feminism and the achievement of feminist objectives? What, if anything, has feminism compromised in order to fit into 140 characters or fewer? This paper argues that social media has provided a platform for feminists to share their stories, which has aided in the building of feminist constituencies. This is the most important work of feminism, because it is making society more receptive to feminist principles and ideas, transforming our culture into one that can accept and fight for feminism's objectives. This paper will examine a series of case studies in which social media has hosted feminist conversations. It will analyze the impact of this social media as a venue for feminist narratives and evaluate the use of social media as a feminist platform in the movement to achieve feminism's objectives.
ContributorsGiel, Katelyn Anne (Author) / Woodall, Gina (Thesis director) / Lake, Milli (Committee member) / School of Politics and Global Studies (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12