Omar Eltayeby

University of North Carolina at Charlotte | UNC Charlotte · Department of Computer Science

This paper describes Pique, a web-based recommendation system that applies word embedding and a sequence generator to present students with a sequence of scientific paper recommendations personalized to their background and interest. The use of natural language processing (NLP) on learning materials enables educational environments to present stude...

Social media content can have extensive online influence [1], but assessing offline influence using online behavior is challenging. Cognitive information processing strategies offer a potential way to code online behavior that may be more predictive of offline preferences, beliefs, and behavior than counting retweets or likes. In this study, we emp...

This study presents the Social Media Cognitive Processing model, which explains and predicts the depth of processing on social media based on three classic concepts from the offline literature about cognitive processing: self-generation, psychological distance, and self-reference. Together, these three dimensions have tremendous explanatory power i...

Binge drinking is a severe health problem faced by many US colleges and universities. College students often post drinking-related text and images on social media, portraying their alcohol use as socially desirable. In this project, we investigated the feasibility of mining the heterogeneous data (e.g. text, images, and videos) on Facebook to ident...

We describe a novel longitudinal study of the frequency and significance of social media users' profile changes. Drawing upon two formative theories from communication and psychology: self-construal and signaling theory, we examine the likelihood that users will change their profiles and what constitutes a significant profile change. Our findings i...

We describe a novel longitudinal study of the frequency and significance of social media users' profile changes. Drawing upon two formative theories from communication and psychology: self-construal and signaling theory, we examine the likelihood that users will change their profiles and what constitutes a significant profile change. Our findings i...

We describe a novel observational study of the frequency and significance of social media users' profile changes. Drawing upon literature from impression management, specifically two formative theories: self-construal and signaling theory, our research examines the likelihood that users will change their profiles, what constitutes a significant pro...

Data models built for analyzing student data often obfuscate temporal relationships for reasons of simplicity, or to aid in generalization. We present a model based on temporal relationships of heterogeneous data as the basis for building predictive models. We show how within- and between-semester temporal patterns can provide insight into the stud...

Background: Society always has limited resources to expend on health care, or anything else. What are the unmet medical needs? How do we allocate limited resources to maximize the health and welfare of the people? These challenging questions might be re-examined systematically within an infodemiological frame on a much larger scale, leveraging the...

One common health problem in the US faced by colleges and universities is binge drinking. College students often post drinking related texts and images on social media as a socially desirable identity. Some public health and clinical research scholars have surveyed different social media sites manually to understand their behavior patterns. In this...

The trend of exploratory visualization development has driven the visual analytics (VA) community to design special evaluation methods. The main goals of these evaluations are to understand the exploration process and improve it by recording users' interactions and thoughts. Some of the recent works have focused on performing manual evaluations of...

The widespread of social media provides unprecedented sources of written language that can be used to model and infer online demo-graphics. In this paper, we introduce a novel visual text analytics system, DemographicVis, to aid interactive analysis of such demographic information based on user-generated content. Our approach connects categorical d...

During the US presidential elections the media played a major role in presenting the candidates’ vision on several topics. Nevertheless, the diversity of opinions along with the political currents, one might notice segregation in opinions among some topics related to each other or a candidate. In the meanwhile, posting opinions on social media coul...

One of the challenging tasks in visual analytics is to target clustered time-series data sets, since it is important for data analysts to discover patterns changing over time while keeping their focus on particular subsets. A web-based application to monitor the Lustre file system for system administrators and operation teams has been developed usi...