Ali Almadan's research while affiliated with University of North Carolina at Charlotte and other places

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Publications (4)

Stance Detection for Gauging Public Opinion: A Statistical Analysis of the Difference Between Tweet-Based and User-Based Stance in Twitter
Chapter
  • Feb 2023
Public opinion provides policy makers with meaningful information on how the public feels towards a certain issue. Stance detection in social media is the problem of automatically determining the standpoint expressed in a specific tweet towards a target of interest such as a topic or an issue. One such application of stance detection is to gauge pu...
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User-Based Stance Analysis for Mitigating the Impact of Social Bots on Measuring Public Opinion with Stance Detection in Twitter
Chapter
  • Oct 2022
Stance detection is the task of detecting the standpoint of a user towards a target of interest, such as a controversial topic. Stance detection has various applications such as surveying and polling the public as an alternative to traditional instruments to measure public opinion. One of the implications of using stance detection on Twitter data t...
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Will You Be Vaccinated? A Methodology for Annotating and Analyzing Twitter Data to Measure the Stance Towards COVID-19 Vaccination
Chapter
  • Mar 2022
People turn to social media to express their opinion towards different topics and issues. This makes social media a valuable resource for mining public opinion. Stance detection is an approach to analyzing social media users’ content to determine public opinion. In this paper, we present a replicable methodology for coding tweets for stance detecti...
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Arny: A Study of a Co-creative Interaction Model Focused on Emotion Feedback
Chapter
  • Oct 2020
This paper presents an AI-based co-creative system in which the interaction model focuses on emotional feedback, that is, the decisions about the creative contribution from the AI agent is based on the emotion detected in the human co-creator. In human-human collaboration, gestures, verbal communications, and emotional responses are among the gener...
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Citations

... This new paradigm is characterized by the mixing of computer and human initiative (Yannakakis et al., 2014) in the middle of a continuum between human creativity and autonomous computational creativity (Deterding et al., 2017). Improving the interaction design with more human-like abilities for conversing and embodied interaction leads to more engaging AI collaboration (Abdellahi et al., 2020;Lee et al., 2020). Despite powerful generative AI methods becoming more and more accessible for designers of creative systems, we still know relatively little about designing interactive generative AI, how to design creative user experiences around them, and the ethical challenges defined by the open-endedness and reuse of creative work. ...
Reference: Perspectives on design creativity and innovation research: 10 years later
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