Browsing by Subject "Twitter"
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Item A critical analysis of contemporary Latinx feminisms on Twitter: an intersectional approach.(2023-01-01) Morte, Maria; Mu–oz, Thania; Modern Languages, Linguistics & Intercultural Communication; Intercultural CommunicationLatinx women face a particular intersectionality of oppression based on gender, ethnicity, and sexual identity. The current capitalist system considers women an oppressed group, and Latinxs experience racial and ethnic discrimination daily. In addition, Latinx culture is male-dominated. Meanwhile, the 21st century has seen a resurgence of the feminist movement, characterized by the adoption of an intersectional framework and the reliance on social networks. To explore how contemporary Latinx feminists address this intersectionality of oppression, this study conducts a Social-Media Critical Discourse Analyst of Latinx feminisms on Twitter, applying a Latinx feminist perspective. It is concluded Latinx feminisms have harnessed the intersectional and digital propellants of the contemporary movement without absorbing neoliberal values and commodifying tendencies. Likewise, their discourses focus on challenging their invisibility by prioritizing the counter-hegemonic narrative of critiquing established power and the strategy of empowering representational power.Item Analyzing Social Media Texts and Images to Assess the Impact of Flash Floods in Cities(IEEE, 2017-06-15) Basnyat, Bipendra; Anam, Amrita; Singh, Neha; Gangopadhyay, Aryya; Roy, NirmalyaComputer Vision and Image Processing are emerging research paradigms. The increasing popularity of social media, micro- blogging services and ubiquitous availability of high-resolution smartphone cameras with pervasive connectivity are propelling our digital footprints and cyber activities. Such online human footprints related with an event-of-interest, if mined appropriately, can provide meaningful information to analyze the current course and pre- and post- impact leading to the organizational planning of various real-time smart city applications. In this paper, we investigate the narrative (texts) and visual (images) components of Twitter feeds to improve the results of queries by exploiting the deep contexts of each data modality. We employ Latent Semantic Analysis (LSA)-based techniques to analyze the texts and Discrete Cosine Transformation (DCT) to analyze the images which help establish the cross-correlations between the textual and image dimensions of a query. While each of the data dimensions helps improve the results of a specific query on its own, the contributions from the dual modalities can potentially provide insights that are greater than what can be obtained from the individual modalities. We validate our proposed approach using real Twitter feeds from a recent devastating flash flood in Ellicott City near the University of Maryland campus. Our results show that the images and texts can be classified with 67\% and 94\% accuracies respectively.Item Analyzing the Sentiment of Crowd for Improving the Emergency Response Services(IEEE, 2018-07-31) Singh, Neha; Roy, Nirmalya; Gangopadhyay, AryyaTwitter is an extremely popular micro-blogging social platform with millions of users, generating thousands of tweets per second. The huge amount of Twitter data inspire the researchers to explore the trending topics, event detection and event tracking which help to postulate the fine-grained details and situation awareness. Obtaining situational awareness of any event is crucial in various application domains such as natural calamities, man made disaster and emergency responses. In this paper, we advocate that data analytics on Twitter feeds can help improve the planning and rescue operations and services as provided by the emergency personnel in the event of unusual circumstances. We take a different approach and focus on the users' emotions, concerns and feelings expressed in tweets during the emergency situations, and analyze those feelings and perceptions in the community involved during the events to provide appropriate feedback to emergency responders and local authorities. We employ sentiment analysis and change point detection techniques to process, discover and infer the spatiotemporal sentiments of the users. We analyze the tweets from recent Las Vegas shooting (Oct. 2017) and note that the changes in the polarity of the sentiments and articulation of the emotional expressions, if captured successfully can be employed as an informative tool for providing feedback to EMS.Item Conspiracies and the 2016 Presidential election: An analysis of Tweets through the lens of agenda-setting theory(2017) Dicks, Darby; Communication ArtsThe introduction of social media websites such as Twitter and Facebook provides users access to platforms in which they are able to express a broad variety of views. It has become increasingly difficult to ignore the expression of these views and beliefs, even the ones that might traditionally be considered niche. The theoretical perspective utilized in this research was agenda-setting theory, which postulates that news media are able to determine issue salience within the public consciousness. This thesis aims to understand (a) how Twitter users articulated conspiratorial beliefs about politics during the 2016 United States presidential election, and (b) how social media has changed the theory of agenda-setting by upsetting traditional dynamics between news media and consumers. User Tweets were collected from Twitter from five different dates between September 27 and November 7 2016, and theme analyzed based on the conspiratorial nature of the content as revealed by the beliefs expressed by individual users. Findings illustrate user beliefs that political forces both internal and external to the United States were conspiring to influence the outcomes of the 2016 election. This study indicates how users of platforms like Twitter can communicate individual belief systems in a way not previously possible under agenda-setting theory as it was previously defined, allowing users to interpret agendas set by news media and share those interpretations with specific audiences. The conspiratorial ideas expressed by Twitter users may point to specific anxieties and fears to be studied further in the future, in addition to a new understanding of agenda-setting theory in the digital age.Item Content-based prediction of temporal boundaries for events in Twitter(IEEE, 2011-10-09) Iyengar, Akshaya; Finin, Tim; Joshi, AnupamSocial media services like Twitter, Flickr and YouTube publish high volumes of user generated content as a major event occurs, making them a potential data source for event analysis. The large volume and noisy content of social media makes automatic preprocessing essential. Intuitively, the eventrelated data falls into three major phases: the buildup to the event, the event itself, and the post-event effects and repercussions. We describe an approach to automatically determine when an anticipated event started and ended by analyzing the content of tweets using an SVM classifier and hidden Markov model. We evaluate our performance by predicting event boundaries on Twitter data for a set of events in the domains of sports, weather and social activities.Item Ebiquity: Paraphrase and Semantic Similarity in Twitter using Skipgram(Association for Computational Linguistics, 2015-06-04) Satyapanich, Taneeya W.; Gao, Hang W.; Finin, TimWe describe the system we developed to participate in SemEval 2015 Task 1, Paraphrase and Semantic Similarity in Twitter. We create similarity vectors from two-skip trigrams of preprocessed tweets and measure their semantic similarity using our UMBC-STS system. We submitted two runs. The best result is ranked eleventh out of eighteen teams with F1 score of 0.599.Item Examining The Relationship Between Social Network Site Use And Persistence Among Students At A Suburban Community College(2014) Spells, Rhonda M.; Ball, Calvin B.; Community College Leadership Program; Doctor of EducationSocial network sites (SNSs) Facebook and Twitter are online communities that college students use extensively for socializing and networking, yet student outcomes associated with the use of these sites has not been fully explored for community college students. Thus, the purpose of this quantitative study was to examine the relationship between SNS use and three key student outcomes--social integration into the college community, commitment to the institution, and persistence at the institution. An additional goal of the study was to assess how community college students use Facebook and Twitter, and to establish a profile of SNS use at the institution. Astin's (1984) theory of student involvement and I-E-O model provided solid frameworks for assessing SNS use to determine its impact on Tinto's (1993) social integration, institutional commitment, and persistence constructs. To quantify SNS use into measures of student time and effort, SNS use was defined as intensity of Facebook and Twitter use, and frequency and type of Facebook and Twitter activities. A 75-item online survey was administered to community college students (n = 364) at a mid-Atlantic suburban community college in the fall 2013 semester. Persistence data, defined as enrollment status in the spring 2014 semester, was provided by the research site's registrar. To address the four research questions, descriptive and inferential statistics were used. Univariate and bivariate analyses were applied to determine SNS use profile characteristics; independent samples t test, analysis of variance, and correlations were used to determine significant differences in SNS use based on demographic characteristics. Pearson product-moment correlation coefficients were computed to assess the relationship between SNS use and social integration and institutional commitment. Hierarchical linear regressions were then used to isolate the specific impact of SNS use beyond the effects of the demographic variables. Hierarchical logistic regression was used to determine the potential predictive relationship between SNS use and persistence. This research confirms that community college students spend a great deal of time on both the Facebook and Twitter and students are actively engaged in various activities on both sites. Significant relationships between SNS use and social integration and institutional commitment were identified. There was no significant relationship between SNS use and persistence. This study revealed limited interaction between students and the institution when using Facebook and Twitter. Other significant findings include differences in SNS use based on age, ethnicity, income level, and attendance goal. This study has implications for how community colleges use the Facebook and Twitter SNSs to interact and engage with students and provides insights into how SNS use is related to positive academic outcomes. Specifically, this study provides evidence that SNSs can be an important strategy for improving student outcomes for African American, Hispanic and low-income students. The results of this study suggests additional research to examine how institutions use SNSs to interact with students will contribute to the understanding of SNS use on community college campuses. To further explore the relationship between SNS use and student outcomes for community college students, research is needed on larger populations representative of the national community college student profile.Item Faking Sandy: Characterizing and Identifying Fake Images on Twitter during Hurricane Sandy(ACM, 2013-05-13) Gupta, Aditi; Lamba, Hemank; Kumaraguru, Ponnurangam; Joshi, AnupamIn today’s world, online social media plays a vital role during real world events, especially crisis events. There are both positive and negative effects of social media coverage of events -- it can be used by authorities for effective disaster management or by malicious entities to spread rumors and fake news. The aim of this paper is to highlight the role of Twitter during Hurricane Sandy (2012) to spread fake images about the disaster. We identified 10,350 unique tweets containing fake images that were circulated on Twitter during Hurricane Sandy. We performed a characterization analysis, to understand the temporal, social reputation and influence patterns for the spread of fake images. Eighty six percent of tweets spreading the fake images were retweets, hence very few were original tweets. Our results showed that top thirty users out of 10,215 users (0.3%) resulted in 90% of the retweets of fake images; also network links, such as follower relationships of Twitter, contributed very less (only 11%) to the spread of these fake photos URLs. Next, we used classification models to distinguish fake images from real images of Hurricane Sandy. Best results were obtained from Decision Tree classifier from which we got 97% accuracy in predicting fake images from real. Also, tweet based features were very effective in distinguishing fake images tweets from real, while the performance of user based features was very poor. Our results showed that automated techniques can be used in identifying real images from fake images posted on Twitter.Item iSkate: A Digital Meet-up for Skateboarders(2024-02-15) King, Derek; Walsh, Greg; Blodgett, Bridget; University of Baltimore. Division of Science, Information Arts and Technologies; University of Baltimore. Master of Science in Interaction Design and Information ArchitectureThis thesis delves into the evolving relationship between skate culture and the digital landscape in our ever-changing technological era. It explores how platforms like Twitter, Facebook, and Thrasher Magazine have reshaped global connections and human interactions, paralleling the remarkable expansion of skateboarding across diverse backgrounds and geographical borders. Skateboarding, once localized, has become a global phenomenon, uniting enthusiasts worldwide under a vibrant subculture. The thesis illuminates how digital spaces act as conduits for immediate information exchange, connecting individuals to the rich tapestry of skate culture. It investigates how these spaces catalyze knowledge-sharing and cultural enrichment.Item Twitter and Higher Education: A Bibliometric AnalysisPrice, Carrie; Towson University. Albert S. Cook Library. Research and InstructionSince the inception of Twitter in 2006, the platform has grown tremendously, with over 199 million daily active users worldwide as of May 2021 (Tankovska, 2021). The use of Twitter in academia is of particular interest to me since I have used the platform to live tweet clinical conferences, to share my professional work, and to connect with large networks of clinicians, medical librarians, and methodologists. These connections have often led to lasting relationships and professional collaborations.Item A UNITED STATE: Moderation. Diversity. Reciprocity. Equality. Designing mobile technology to support productive online political discourse.(2019-05) Bend, Justin; Summers, Kathryn; Walsh, Greg; Fioramonti, Joseph; Pointer, Amy; University of Baltimore. Yale Gordon College of Arts and Sciences; Master of Fine Arts in Integrated DesignI have endeavored upon this thesis work in an attempt to find design solutions to the pressing societal problems of ever-increasing political polarization coupled with widespread dissatisfaction with social media’s effect on our political discourse. As an outcome of my efforts, I have designed an interactive prototype proof of concept for a mobile application whose goal is to increase productivity in online political discourse by moderating human behavior to guarantee equal speaking time for all participants, matching real and diverse members together based on differences of belief rather than similarities. The application would use the mobile device camera and microphone to facilitate face-to-face, eye-to-eye conversations between people in the United States while protecting member identification and privacy, safeguarding against abuse.