Social Media Commons^™

Unveiling The Dynamics Of Crisis Events: Sentiment And Emotion Analysis Via Multi-Task Learning With Attention Mechanism And Subject-Based Intent Prediction, Phyo Yi Win Myint, Siaw Ling Lo, Yuhao Zhang

Research Collection School Of Computing and Information Systems

In the age of rapid internet expansion, social media platforms like Twitter have become crucial for sharing information, expressing emotions, and revealing intentions during crisis situations. They offer crisis responders a means to assess public sentiment, attitudes, intentions, and emotional shifts by monitoring crisis-related tweets. To enhance sentiment and emotion classification, we adopt a transformer-based multi-task learning (MTL) approach with attention mechanism, enabling simultaneous handling of both tasks, and capitalizing on task interdependencies. Incorporating attention mechanism allows the model to concentrate on important words that strongly convey sentiment and emotion. We compare three baseline models, and our findings show that …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

The Socialization Of Social Media: Examining The Impact Of Social Media Use On Interpersonal Skills During Face-To-Face Interaction, Tenille Thomas

Masters Theses & Specialist Projects

Research has well established that the use of social networking sites (SNS) has increased accessibility and connectivity to people with limitless boundaries. SNS have progressively become the preferred source of communication. However, often overlooked is the impact SNS use has on face-to-face interactions, specifically on interpersonal skills. The purpose of this study was to examine the relationship between SNS use and face-to-face interaction. Specifically, this study examines the participant’s ability to recognize and interpret nonverbal cues with increased SNS use. This was a correlational study utilizing a quantitative design of self-reported questionnaires. A total of 178 participants, ranging in age …

Transformer-Based Multi-Task Learning For Crisis Actionability Extraction, Yuhao Zhang, Siaw Ling Lo, Phyo Yi Win Myint

Research Collection School Of Computing and Information Systems

Social media has become a valuable information source for crisis informatics. While various methods were proposed to extract relevant information during a crisis, their adoption by field practitioners remains low. In recent fieldwork, actionable information was identified as the primary information need for crisis responders and a key component in bridging the significant gap in existing crisis management tools. In this paper, we proposed a Crisis Actionability Extraction System for filtering, classification, phrase extraction, severity estimation, localization, and aggregation of actionable information altogether. We examined the effectiveness of transformer-based LSTM-CRF architecture in Twitter-related sequence tagging tasks and simultaneously extracted actionable …

Experiences Of Autistic Twitch Livestreamers: “I Have Made Easily The Most Meaningful And Impactful Relationships”, Terrance Mok, Anthony Tang, Adam Mccrimmon, Lora Oehlberg

Research Collection School Of Computing and Information Systems

We present perspectives from 10 autistic Twitch streamers regarding their experiences as livestreamers and how autism uniquely colors their experiences. Livestreaming offers a social online experience distinct from in-person, face-to-face communication, where autistic people tend to encounter challenges. Our reflexive thematic analysis of interviews with 10 participants showcases autistic livestreamers’ perspectives in their own words. Our findings center on the importance of having streamers establishing connections with other, sharing autistic identities, controlling a space for social interaction, personal growth, and accessibility challenges. In our discussion, we highlight the crucial value of having a medium for autistic representation, as well as …

#Disruptjmm: Online Social Justice Advocacy And Community Building In Mathematics, Rachel Roca, Carrie Diaz Eaton, Drew Lewis, Joseph Hibdon, Stefanie Marshall

Journal of Humanistic Mathematics

In 2019, \#DisruptJMM, a Twitter hashtag, began circulating after an Inclusion/Exclusion blog by Dr. Piper H pointing to the need to make commonplace conversations about human suffering in the Joint Mathematics Meetings (JMM). While the \#DisruptJMM hashtag has been used since 2019, the vast majority of use was in the JMM 2020 meetings. Twitter hashtags are used by activists to push forward conversations, join communities around a single idea, and create change. In this article, we draw on frameworks from community building seen in other equity and inclusion advocacy hashtags such as \#GirlsLikeUs [7] to qualitatively code and analyze tweets …

Impact Of Difficult Negatives On Twitter Crisis Detection, Yuhao Zhang, Siaw Ling Lo, Phyo Yi Win Myint

Research Collection School Of Computing and Information Systems

Twitter has become an alternative information source during a crisis. However, the short, noisy nature of tweets hinders information extraction. While models trained with standard Twitter crisis datasets accomplished decent performance, it remained a challenge to generalize to unseen crisis events. Thus, we proposed adding “difficult” negative examples during training to improve model generalization for Twitter crisis detection. Although adding random noise is a common practice, the impact of difficult negatives, i.e., negative data semantically similar to true examples, was never examined in NLP. Most of existing research focuses on the classification task, without considering the primary information need of …

Hacker, Influencer, Counter-Culture Spy: Cyberspace Actors’ Models Of Misinformation And Counter-Operations, Benjamin Kessell

College of Computing and Digital Media Dissertations

As misinformation continues to spread on social media, its residents have begun to fight back, independent of any platform. This organic resistance to the diffusion of misinformation is a clearly observable phenomenon with roots in Anonymous’ distributed campaigns from the 2010s outwards. Hacker and information security communities are acting in defense of some of their favorite spaces, most notably, Twitter. Security researchers of all stripes use it for sharing indicators of compromise but, as the diffusion of misinformation becomes more problematic it becomes more difficult to find signals in the noise.

These actors’ response to the issues at hand is …

Resale Hdb Price Prediction Considering Covid-19 Through Sentiment Analysis, Srinaath Anbu Durai, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

Twitter sentiment has been used as a predictor to predict price values or trends in both the stock market and housing market. The pioneering works in this stream of research drew upon works in behavioural economics to show that sentiment or emotions impact economic decisions. Latest works in this stream focus on the algorithm used as opposed to the data used. A literature review of works in this stream through the lens of data used shows that there is a paucity of work that considers the impact of sentiments caused due to an external factor on either the stock or …

Identifying Social Media Users That Are Susceptible To Phishing Attacks, Zoe Metzger

Undergraduate Honors Theses

Phishing scams are a billion-dollar problem. According to Threatpost, in 2020, business email compromise phishing attacks cost the US economy $ 1.8 billion. Social media phishing scams are also on the rise with 74% of companies experiencing social media attacks in 2021 according to Proofpoint. Educating users about phishing scams is an effective strategy for reducing phishing attacks. Despite efforts to combat phishing, the number of attacks continues to rise, likely indicative of a reticence of users to change online behaviors. Existing research into predicting vulnerable social media users that are susceptible to phishing mostly focuses on content analysis of …

Supporting Account-Based Queries For Archived Instagram Posts, Himarsha R. Jayanetti

Computer Science Theses & Dissertations

Social media has become one of the primary modes of communication in recent times, with popular platforms such as Facebook, Twitter, and Instagram leading the way. Despite its popularity, Instagram has not received as much attention in academic research compared to Facebook and Twitter, and its significant role in contemporary society is often overlooked. Web archives are making efforts to preserve social media content despite the challenges posed by the dynamic nature of these sites. The goal of our research is to facilitate the easy discovery of archived copies, or mementos, of all posts belonging to a specific Instagram account …

Extracting Information From Twitter Screenshots, Tarannum Zaki, Michael L. Nelson, Michele C. Weigle

Modeling, Simulation and Visualization Student Capstone Conference

Screenshots are prevalent on social media as a common approach for information sharing. Users rarely verify before sharing screenshots whether they are fake or real. Information sharing through fake screenshots can be highly responsible for misinformation and disinformation spread on social media. There are services of the live web and web archives that could be used to validate the content of a screenshot. We are going to develop a tool that would automatically provide a probability whether a screenshot is fake by using the services of the live web and web archives.

Behind Derogatory Migrants' Terms For Venezuelan Migrants: Xenophobia And Sexism Identification With Twitter Data And Nlp, Joseph Martínez, Melissa Miller-Felton, Jose Padilla, Erika Frydenlund

Modeling, Simulation and Visualization Student Capstone Conference

The sudden arrival of many migrants can present new challenges for host communities and create negative attitudes that reflect that tension. In the case of Colombia, with the influx of over 2.5 million Venezuelan migrants, such tensions arose. Our research objective is to investigate how those sentiments arise in social media. We focused on monitoring derogatory terms for Venezuelans, specifically veneco and veneca. Using a dataset of 5.7 million tweets from Colombian users between 2015 and 2021, we determined the proportion of tweets containing those terms. We observed a high prevalence of xenophobic and defamatory language correlated with the …

Learning-Based Stock Trending Prediction By Incorporating Technical Indicators And Social Media Sentiment, Zhaoxia Wang, Zhenda Hu, Fang Li, Seng-Beng Ho, Erik Cambria

Research Collection School Of Computing and Information Systems

Stock trending prediction is a challenging task due to its dynamic and nonlinear characteristics. With the development of social platform and artificial intelligence (AI), incorporating timely news and social media information into stock trending models becomes possible. However, most of the existing works focus on classification or regression problems when predicting stock market trending without fully considering the effects of different influence factors in different phases. To address this gap, this research solves stock trending prediction problem utilizing both technical indicators and sentiments of the social media text as influence factors in different situations. A 3-phase hybrid model is proposed …

Environmental Activism: Pro-Environmental Behavior, Consumerism, And Environmental Justice, Kaden Uribe, April Chapman-Ludwig

DU Undergraduate Research Journal Archive

This literature review examines established research on the concept of pro-environmental behaviors (PEB) and its subsects: activism and consumerism. There are competing opinions regarding the salience of pro-environmental activist behavior. This dichotomy is characterized by the role of social media, which can be simultaneously used for performative identity signaling and as a platform to facilitate global collective activism. The research shows a stark contrast between pro-environmental activism and pro-environmental consumerism, with the former acknowledging historical injustices and addressing the social, economic, and environmental disparities created by neo-liberal policies designed with the purpose of profit extraction at the expense of marginalized …

Enabling Customization Of Discussion Forums For Blind Users, Mohan Sunkara, Yash Prakash, Hae-Na Lee, Sampath Jayarathna, Vikas Ashok

Computer Science Faculty Publications

Online discussion forums have become an integral component of news, entertainment, information, and video-streaming websites, where people all over the world actively engage in discussions on a wide range of topics including politics, sports, music, business, health, and world affairs. Yet, little is known about their usability for blind users, who aurally interact with the forum conversations using screen reader assistive technology. In an interview study, blind users stated that they often had an arduous and frustrating interaction experience while consuming conversation threads, mainly due to the highly redundant content and the absence of customization options to selectively view portions …

S-400s, Disinformation, And Anti-American Sentiment In Turkey, Russell "Alex" Korb, Saltuk Karahan, Gowri Prathap, Ekrem Kaya, Luke Palmieri, Hamdi Kavak, Richard L. Wilson (Ed.), Major Brendan Curran (Ed.)

Political Science & Geography Faculty Publications

As social and political discourse in most countries becomes more polarized, anti-Americanism has risen not only in the Middle East and Latin America but also among the U.S. allies in Europe. Social media is one platform used to disseminate anti-American views in NATO countries, and its effectiveness can be magnified when mass media, public officials, and popular figures adopt these views. Disinformation, in particular, has gained recognition as a cybersecurity issue from 2016 onward, but disinformation can be manufactured domestically in addition to being part of a foreign influence campaign. In this paper, we analyze Turkish tweets using sentiment analysis …

Investigating Collaborative Explainable Ai (Cxai)/Social Forum As An Explainable Ai (Xai) Method In Autonomous Driving (Ad), Tauseef Ibne Mamun

Dissertations, Master's Theses and Master's Reports

Explainable AI (XAI) systems primarily focus on algorithms, integrating additional information into AI decisions and classifications to enhance user or developer comprehension of the system's behavior. These systems often incorporate untested concepts of explainability, lacking grounding in the cognitive and educational psychology literature (S. T. Mueller et al., 2021). Consequently, their effectiveness may be limited, as they may address problems that real users don't encounter or provide information that users do not seek.

In contrast, an alternative approach called Collaborative XAI (CXAI), as proposed by S. Mueller et al (2021), emphasizes generating explanations without relying solely on algorithms. CXAI centers …

Champions For Social Good: How Can We Discover Social Sentiment And Attitude-Driven Patterns In Prosocial Communication?, Raghava Rao Mukkamala, Robert J. Kauffman, Helle Zinner Henriksen

Research Collection School Of Computing and Information Systems

The UN High Commissioner on Refugees (UNHCR) is pursuing a social media strategy to inform people about displaced populations and refugee emergencies. It is actively engaging public figures to increase awareness through its prosocial communications and improve social informedness and support for policy changes in its services. We studied the Twitter communications of UNHCR social media champions and investigated their role as high-profile influencers. In this study, we offer a design science research and data analytics framework and propositions based on the social informedness theory we propose in this paper to assess communication about UNHCR’s mission. Two variables—refugee-emergency and champion …

Is A Pretrained Model The Answer To Situational Awareness Detection On Social Media?, Siaw Ling Lo, Kahhe Lee, Yuhao Zhang

Research Collection School Of Computing and Information Systems

Social media can be valuable for extracting information about an event or incident on the ground. However, the vast amount of content shared, and the linguistic variants of languages used on social media make it challenging to identify important situational awareness content to aid in decision-making for first responders. In this study, we assess whether pretrained models can be used to address the aforementioned challenges on social media. Various pretrained models, including static word embedding (such as Word2Vec and GloVe) and contextualized word embedding (such as DistilBERT) are studied in detail. According to our findings, a vanilla DistilBERT pretrained language …

Discourse, Power Dynamics, And Risk Amplification In Disaster Risk Management In Canada, Martins Oluwole Olu-Omotayo

Electronic Thesis and Dissertation Repository

The domain of disaster risk management is rife with discursive contentions, whereby dominant discourses amplify the powers of risk actors to precipitate and reinforce political, economic, and environmental inequalities that predispose different sections of the population to unequal disaster risk vulnerabilities. This thesis identified important actors (government, risk experts, media, and NGOs) that shape the power dynamics in disaster risk management in Canada and explained their roles, influences, and the dimensions in which their powers negotiate each other through risk discourses. The patterns of these power dynamics in the three aspects of power –communication, assessment, and social trust –were also …

Bounded Confidence: How Ai Could Exacerbate Social Media’S Homophily Problem, Dylan Weber, Scott Atran, Rich Davis

New England Journal of Public Policy

The advent of the Internet was heralded as a revolutionary development in the democratization of information. It has emerged, however, that online discourse on social media tends to narrow the information landscape of its users. This dynamic is driven by the propensity of the network structure of social media to tend toward homophily; users strongly prefer to interact with content and other users that are similar to them. We review the considerable evidence for the ubiquity of homophily in social media, discuss some possible mechanisms for this phenomenon, and present some observed and hypothesized effects. We also discuss how the …

Does Social Media Accelerate Product Recalls? Evidence From The Pharmaceutical Industry, Yang Gao, Wenjing Duan, Huaxia Rui

Research Collection School Of Computing and Information Systems

Social media has become a vital platform for voicing product-related experiences that may not only reveal product defects but also impose pressure on firms to act more promptly than before. This study scrutinizes the rarely-studied relationship between these voices and the speed of product recalls in the context of the pharmaceutical industry where social media pharmacovigilance is becoming increasingly important for the detection of drug safety signals. Using Federal Drug Administration (FDA) drug enforcement reports and social media data crawled from online forums and Twitter, we investigate whether social media can accelerate the product recall process in the context of …

Analyzing Fluctuation Of Topics And Public Sentiment Through Social Media Data, Haoyue Liu

Dissertations

Over the past decade years, Internet users were expending rapidly in the world. They form various online social networks through such Internet platforms as Twitter, Facebook and Instagram. These platforms provide a fast way that helps their users receive and disseminate information and express personal opinions in virtual space. When dealing with massive and chaotic social media data, how to accurately determine what events or concepts users are discussing is an interesting and important problem.

This dissertation work mainly consists of two parts. First, this research pays attention to mining the hidden topics and user interest trend by analyzing real-world …

Spectral Analysis Of Multiscale Cultural Traits On Twitter, Chandler Squires, Nikhil Kunapuli, Yaneer Bar-Yam, Alfredo Morales

Northeast Journal of Complex Systems (NEJCS)

Understanding and mapping the emergence and boundaries of cultural areas is a challenge for social sciences. In this paper, we present a method for analyzing the cultural composition of regions via Twitter hashtags. Cultures can be described as distinct combination of traits which we capture via principal component analysis (PCA). We investigate the top 8 PCA components of an area including France, Spain, and Portugal, in terms of the geographic distribution of their hashtag composition. We also discuss relationships between components and the insights those relationships can provide into the structure of a cultural space. Finally, we compare the spatial …

A Large-Scale Sentiment Analysis Of Tweets Pertaining To The 2020 Us Presidential Election, Rao Hamza Ali, Gabriela Pinto, Evelyn Lawrie, Erik J. Linstead

Engineering Faculty Articles and Research

We capture the public sentiment towards candidates in the 2020 US Presidential Elections, by analyzing 7.6 million tweets sent out between October 31st and November 9th, 2020. We apply a novel approach to first identify tweets and user accounts in our database that were later deleted or suspended from Twitter. This approach allows us to observe the sentiment held for each presidential candidate across various groups of users and tweets: accessible tweets and accounts, deleted tweets and accounts, and suspended or inaccessible tweets and accounts. We compare the sentiment scores calculated for these groups and provide key insights into the …

Why, New York City? Gauging The Quality Of Life Through The Thoughts Of Tweeters, Sheryl Williams

Dissertations, Theses, and Capstone Projects

As a resource for social data, Twitter’s platform has been used to measure the quality of life through sentiment analysis. This capstone project explores another methodological technique—querying Twitter data around specific keyword terms to determine dominant topics, word patterns, and sentiment leanings in a geographical area. Focusing on New York City and Los Angeles for comparative analysis, the keyword term “why” will be used to build a Python analysis around topic modeling and sentiment analysis. Using this approach, the analysis reveals social and cultural differences, the overall sentiment of tweets, and subjects of interest to tweeters.

GitHub Repository for all …

Storm The Capitol: Linking Offline Political Speech And Online Twitter Extra-Representational Participation On Qanon And The January 6 Insurrection, Claire Seungeun Lee, Juan Merizalde, John D. Colautti, Jisun An, Haewoon Kwak

Research Collection School Of Computing and Information Systems

The transfer of power stemming from the 2020 presidential election occurred during an unprecedented period in United States history. Uncertainty from the COVID-19 pandemic, ongoing societal tensions, and a fragile economy increased societal polarization, exacerbated by the outgoing president's offline rhetoric. As a result, online groups such as QAnon engaged in extra political participation beyond the traditional platforms. This research explores the link between offline political speech and online extra-representational participation by examining Twitter within the context of the January 6 insurrection. Using a mixed-methods approach of quantitative and qualitative thematic analyses, the study combines offline speech information with Twitter …

Tiktok As A Digital Activism Space: Social Justice Under Algorithmic Control, Brittany Haslem

Institute for the Humanities Theses

TikTok, a video sharing application, has become the center of viral internet culture. The app has risen in popularity so quickly that scholarly literature investigating its vast societal impact is still nascent. TikTok is not only used to discuss popular culture topics and create trends, but also being utilized as a tool for social justice activism in the United States in the wake of a tumultuous year with major events such as the coronavirus pandemic, a resurgence of the Black Lives Matter movement, and the 2020 presidential election. TikTok activism is not without critiques, ranging from concerns of foreign government …

How Online Platforms Are Used By Child Predators And What Are The Effective Preventive Measures?, Kayla Macpherson

Cybersecurity Undergraduate Research Showcase

As technology has evolved greatly in the twenty-first century alone, younger generations have had an opportunity to grow up with devices at their fingertips none have ever before. This accessibility has strengthened their ability of quick use, skill, and a strong feeling of comfort with using and having access to technology. There seems to be more children with access to the internet than there are without, but there is also an ongoing issue behind the screens.