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Social and Behavioral Sciences Commons™
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- Accessibility technologies (1)
- Assistive technology (1)
- Attacks Models (1)
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- Empirical studies in accessibility (1)
- Fact-Proposition Space Inferences (1)
- Feature extraction; information credibility; online social networks; predictive models (1)
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Articles 1 - 7 of 7
Full-Text Articles in Social and Behavioral Sciences
Enabling Customization Of Discussion Forums For Blind Users, Mohan Sunkara, Yash Prakash, Hae-Na Lee, Sampath Jayarathna, Vikas Ashok
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 …
Understanding The Impact Of Encrypted Dns On Internet Censorship, Lin Jin, Shuai Hao, Haining Wang, Chase Cotton
Understanding The Impact Of Encrypted Dns On Internet Censorship, Lin Jin, Shuai Hao, Haining Wang, Chase Cotton
Computer Science Faculty Publications
DNS traffic is transmitted in plaintext, resulting in privacy leakage. To combat this problem, secure protocols have been used to encrypt DNS messages. Existing studies have investigated the performance overhead and privacy benefits of encrypted DNS communications, yet little has been done from the perspective of censorship. In this paper, we study the impact of the encrypted DNS on Internet censorship in two aspects. On one hand, we explore the severity of DNS manipulation, which could be leveraged for Internet censorship, given the use of encrypted DNS resolvers. In particular, we perform 7.4 million DNS lookup measurements on 3,813 DoT …
Ssentiaa: A Self-Supervised Sentiment Analyzer For Classification From Unlabeled Data, Salim Sazzed, Sampath Jayarathna
Ssentiaa: A Self-Supervised Sentiment Analyzer For Classification From Unlabeled Data, Salim Sazzed, Sampath Jayarathna
Computer Science Faculty Publications
In recent years, supervised machine learning (ML) methods have realized remarkable performance gains for sentiment classification utilizing labeled data. However, labeled data are usually expensive to obtain, thus, not always achievable. When annotated data are unavailable, the unsupervised tools are exercised, which still lag behind the performance of supervised ML methods by a large margin. Therefore, in this work, we focus on improving the performance of sentiment classification from unlabeled data. We present a self-supervised hybrid methodology SSentiA (Self-supervised Sentiment Analyzer) that couples an ML classifier with a lexicon-based method for sentiment classification from unlabeled data. We first introduce LRSentiA …
Detecting Incentivized Review Groups With Co-Review Graph, Yubao Zhang, Shuai Hao, Haining Wang
Detecting Incentivized Review Groups With Co-Review Graph, Yubao Zhang, Shuai Hao, Haining Wang
Computer Science Faculty Publications
Online reviews play a crucial role in the ecosystem of nowadays business (especially e-commerce platforms), and have become the primary source of consumer opinions. To manipulate consumers’ opinions, some sellers of e-commerce platforms outsource opinion spamming with incentives (e.g., free products) in exchange for incentivized reviews. As incentives, by nature, are likely to drive more biased reviews or even fake reviews. Despite e-commerce platforms such as Amazon have taken initiatives to squash the incentivized review practice, sellers turn to various social networking platforms (e.g., Facebook) to outsource the incentivized reviews. The aggregation of sellers who …
Rating News Claims: Feature Selection And Evaluation, Izzat Alsmadi, Michael J. O'Brien
Rating News Claims: Feature Selection And Evaluation, Izzat Alsmadi, Michael J. O'Brien
Computer Science Faculty Publications
News claims that travel the Internet and online social networks (OSNs) originate from different, sometimes unknown sources, which raises issues related to the credibility of those claims and the drivers behind them. Fact-checking websites such as Snopes, FactCheck, and Emergent use human evaluators to investigate and label news claims, but the process is labor- and time-intensive. Driven by the need to use data analytics and algorithms in assessing the credibility of news claims, we focus on what can be generalized about evaluating human-labeled claims. We developed tools to extract claims from Snopes and Emergent and used public datasets collected by …
Characteristics Of Social Media Stories, Yasmin Ainoamany, Michele C. Weigle, Michael L. Nelson
Characteristics Of Social Media Stories, Yasmin Ainoamany, Michele C. Weigle, Michael L. Nelson
Computer Science Faculty Publications
An emerging trend in social media is for users to create and publish "stories", or curated lists of web resources with the purpose of creating a particular narrative of interest to the user. While some stories on the web are automatically generated, such as Facebook’s "Year in Review", one of the most popular storytelling services is "Storify", which provides users with curation tools to select, arrange, and annotate stories with content from social media and the web at large. We would like to use tools like Storify to present automatically created summaries of archival collections. To support automatic story creation, …
A Social Dimensional Cyber Threat Model With Formal Concept Analysis And Fact-Proposition Inference, Anup Sharma, Robin Gandhi, Qiuming Zhu, William Mahoney, William Sousan
A Social Dimensional Cyber Threat Model With Formal Concept Analysis And Fact-Proposition Inference, Anup Sharma, Robin Gandhi, Qiuming Zhu, William Mahoney, William Sousan
Computer Science Faculty Publications
Cyberspace has increasingly become a medium to express outrage, conduct protests, take revenge, spread opinions, and stir up issues. Many cyber attacks can be linked to current and historic events in the social, political, economic, and cultural (SPEC) dimensions of human conflicts in the physical world. These SPEC factors are often the root cause of many cyber attacks. Understanding the relationships between past and current SPEC events and cyber attacks can help understand and better prepare people for impending cyber attacks. The focus of this paper is to analyze these attacks in social dimensions and build a threat model based …