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Full-Text Articles in Physical Sciences and Mathematics
Perception Of Bias In Chatgpt: Analysis Of Social Media Data, Abdullah Wahbeh, Mohammad A. Al-Ramahi, Omar El-Gayar, Ahmed El Noshokaty, Tareq Nasralah
Perception Of Bias In Chatgpt: Analysis Of Social Media Data, Abdullah Wahbeh, Mohammad A. Al-Ramahi, Omar El-Gayar, Ahmed El Noshokaty, Tareq Nasralah
Computer Information Systems Faculty Publications
In this study, we aim to analyze the public perception of Twitter users with respect to the use of ChatGPT and the potential bias in its responses. Sentiment and emotion analysis were also analyzed. Analysis of 5,962 English tweets showed that Twitter users were concerned about six main types of biases, namely: political, ideological, data & algorithmic, gender, racial, cultural, and confirmation biases. Sentiment analysis showed that most of the users reflected a neutral sentiment, followed by negative and positive sentiment. Emotion analysis mainly reflected anger, disgust, and sadness with respect to bias concerns with ChatGPT use.
Phishing In The Free Waters: A Study Of Phishing Attacks Created Using Free Website Building Services, Sayak Saha Roy, Karanjit Unique, Shirin Nilizadeh
Phishing In The Free Waters: A Study Of Phishing Attacks Created Using Free Website Building Services, Sayak Saha Roy, Karanjit Unique, Shirin Nilizadeh
Computer Science and Engineering Faculty Publications
Free Website Building services (FWBs) provide individuals with a cost-effective and convenient way to create a website without requiring advanced technical knowledge or coding skills. However, malicious actors often abuse these services to host phishing websites. In this work, we propose FreePhish, a scalable framework to continuously identify phishing websites that are created using FWBs. Using FreePhish, we were able to detect and characterize more than 31.4K phishing URLs that were created using 17 unique free website builder services and shared on Twitter and Facebook over a period of six months. We find that FWBs provide attackers with several features …
Building Credibility, Trust, And Safety On Video-Sharing Platforms, Shuo Niu, Zhicong Lu, Amy X. Zhang, Jie Cai, Carla F. Griggio, Hendrick Heuer
Building Credibility, Trust, And Safety On Video-Sharing Platforms, Shuo Niu, Zhicong Lu, Amy X. Zhang, Jie Cai, Carla F. Griggio, Hendrick Heuer
Computer Science
Video-sharing platforms (VSPs) such as YouTube, TikTok, and Twitch attract millions of users and have become influential information sources, especially among the young generation. Video creators and live streamers make videos to engage viewers and form online communities. VSP celebrities obtain monetary benefits through monetization programs and affiliated markets. However, there is a growing concern that user-generated videos are becoming a vehicle for spreading misinformation and controversial content. Creators may make inappropriate content for attention and financial benefits. Some other creators also face harassment and attack. This workshop seeks to bring together a group of HCI scholars to brainstorm technical …
One Theme, Infinite Interpretations. Exploring Perspective Through Photo Sharing., Avery Gosselin
One Theme, Infinite Interpretations. Exploring Perspective Through Photo Sharing., Avery Gosselin
Honors College
In this creative Honors Thesis project, I have developed an initial, beta version, of an application that celebrates diverse perspectives through photo sharing within an interactive mobile interface. This application, titled NüLens and developed using the React Native framework, takes the form of a participatory digital art project, where members of the public have captured and submitted photos that (in their eyes) represent a predefined theme (in this initial release, the theme of nature). These photos were then aggregated into a mosaic of all other user-submitted photos relating to that theme, along with options to filter and sort the images …
Of Stances, Themes, And Anomalies In Covid-19 Mask-Wearing Tweets, Jwen Fai Low, Benjamin C.M. Fung, Farkhund Iqbal, Ebrahim Bagheri
Of Stances, Themes, And Anomalies In Covid-19 Mask-Wearing Tweets, Jwen Fai Low, Benjamin C.M. Fung, Farkhund Iqbal, Ebrahim Bagheri
All Works
COVID-19 is an opportunity to study public acceptance of a ‘‘new’’ healthcare intervention, universal masking, which unlike vaccination, is mostly alien to the Anglosphere public despite being practiced in ages past. Using a collection of over two million tweets, we studied the ways in which proponents and opponents of masking vied for influence as well as the themes driving the discourse. Pro-mask tweets encouraging others to mask up dominated Twitter early in the pandemic though its continued dominance has been eroded by anti-mask tweets criticizing others for their masking behavior. Engagement, represented by the counts of likes, retweets, and replies, …
Social Media Bot Detection With Deep Learning Methods: A Systematic Review, Kadhim Hayawi, Susmita Saha, Mohammad Mehedy Masud, Sujith Samuel Mathew, Mohammed Kaosar
Social Media Bot Detection With Deep Learning Methods: A Systematic Review, Kadhim Hayawi, Susmita Saha, Mohammad Mehedy Masud, Sujith Samuel Mathew, Mohammed Kaosar
All Works
Social bots are automated social media accounts governed by software and controlled by humans at the backend. Some bots have good purposes, such as automatically posting information about news and even to provide help during emergencies. Nevertheless, bots have also been used for malicious purposes, such as for posting fake news or rumour spreading or manipulating political campaigns. There are existing mechanisms that allow for detection and removal of malicious bots automatically. However, the bot landscape changes as the bot creators use more sophisticated methods to avoid being detected. Therefore, new mechanisms for discerning between legitimate and bot accounts are …
Leveraging Machine Learning To Analyze Sentiment From Covid-19 Tweets: A Global Perspective, Md Mahbubar Rahman, Nafiz Imtiaz Khan, Iqbal H. Sarker, Mohiuddin Ahmed, Muhammad Nazrul Islam
Leveraging Machine Learning To Analyze Sentiment From Covid-19 Tweets: A Global Perspective, Md Mahbubar Rahman, Nafiz Imtiaz Khan, Iqbal H. Sarker, Mohiuddin Ahmed, Muhammad Nazrul Islam
Research outputs 2022 to 2026
Since the advent of the worldwide COVID-19 pandemic, analyzing public sentiment has become one of the major concerns for policy and decision-makers. While the priority is to curb the spread of the virus, mass population (user) sentiment analysis is equally important. Though sentiment analysis using different state-of-the-art technologies has been focused on during the COVID-19 pandemic, the reasons behind the variations in public sentiment are yet to be explored. Moreover, how user sentiment varies due to the COVID-19 pandemic from a cross-country perspective has been less focused on. Therefore, the objectives of this study are: to identify the most effective …