Physical Sciences and Mathematics Commons^™

The Social Pot: A Social Media Application, Reid Long

Honors Projects

The Social Pot is a web application that allows a user to post to Instagram and X simultaneously from one place. The user creates a Social Pot Account and from there can set their Instagram username and password within the home page. Once the user attempts to post, it will redirect them to login to X which once successful will make the tweet. Used the API 'instagram-private-api'. User needed to give access to my X Project which in turn gave an Auth token (via X redirect URL). The auth token was then sent to my endpoint in order to get …

The Social Pot: A Social Media Application, Reid Long

ASPIRE 2024

The Social Pot is a web application that allows a user to post to Instagram and X simultaneously from one place. The user creates a Social Pot Account and from there can set their Instagram username and password within the home page. Once the user attempts to post, it will redirect them to login to X which once successful will make the tweet. Used the API 'instagram-private-api'. User needed to give access to my X Project which in turn gave an Auth token (via X redirect URL). The auth token was then sent to my endpoint in order to get …

Why Do We Not Stand Up To Misinformation? Factors Influencing The Likelihood Of Challenging Misinformation On Social Media And The Role Of Demographics, Selin Gurgun, Deniz Cemiloglu, Emily Arden Close, Keith Phalp, Preslav Nakov, Raian Ali

Natural Language Processing Faculty Publications

This study investigates the barriers to challenging others who post misinformation on social media platforms. We conducted a survey amongst U.K. Facebook users (143 (57.2 %) women, 104 (41.6 %) men) to assess the extent to which the barriers to correcting others, as identified in literature across disciplines, apply to correcting misinformation on social media. We also group the barriers into factors and explore demographic differences amongst them. It has been suggested that users are generally hesitant to challenge misinformation. We found that most of our participants (58.8 %) were reluctant to challenge misinformation. We also identified moderating roles of …

Emoji Use In Social Media Posts: Relationships With Personality Traits And Word Usage, Shelia Kennison, Kameryn Fritz, Maria Andrea Hurtado Morales, Eric Chan-Tin

Computer Science: Faculty Publications and Other Works

Prior research has demonstrated relationships between personality traits of social media users and the language used in their posts. Few studies have examined whether there are relationships between personality traits of users and how they use emojis in their social media posts. Emojis are digital pictographs used to express ideas and emotions. There are thousands of emojis, which depict faces with expressions, objects, animals, and activities. We conducted a study with two samples (n = 76 and n = 245) in which we examined how emoji use on X (formerly Twitter) related to users’ personality traits and language use …

Developing A Success Model Of A Social Student Relationship Management System, Wasef Mater, Monther Aldwairi, Nasim Matar, Waleed Al-Rahmi

All Works

Social media's significance in higher education has increased due to its capacity to enhance participation, communication, teamwork, and information sharing. Important notifications, updates, and reminders can be promptly received by all members of the university community, assuring that information is shared with everyone. The objective of this study is to develop a model for a Customer Relationship Management (CRM) system in higher education that is based on social media and intends to increase student satisfaction, loyalty, and profitability. It blends the idea of trust with Delone Mclean success model. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to evaluate the …

Higher Education Faculty Perceptions Of Chatgpt And The Influencing Factors: A Sentiment Analysis Of X, Yoseph Mamo, Helen Crompton, Diane Burke, Christine E. Nickel

STEMPS Faculty Publications

ChatGPT, an AI chatbot developed by OpenAI, was released in November 2022, sparking a significant surge in global awareness and utilization of generative AI across various domains. Although recent studies have acknowledged the significance of ChatGPT in the education sector, they have yet to focus on exploring faculty attitudes toward ChatGPT. We gathered a comprehensive corpus of tweets containing “#ChatGPT” and “#highered” between November 30th, 2022, and April 30th, 2023. We analyzed data by triangulating VADER, NRC lexicon, and ground coding. Findings suggest that 40% of the expressed sentiments were positive, 51% were neutral, and 9% were negative. The study …

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.

Use Of Social Media During The Covid-19 Pandemic Of 2020, Aliya Goncalves Almeida

Honors Program Theses and Projects

Nowadays billions of people use social media platforms as a way to keep in touch with family and friends, fill spare time, find content, find inspiration for things to do and buy, share, and discuss opinions with others, and the list goes on. This project focused and investigated on the use of social media during the years, in particular during quarantine/lockdown. Utilizing the public source data, I explored several research questions including how many hours people spent on social media, the popularity of social media apps, as well as what age group uses social media platforms (teenagers, young adults, adults). …

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

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 …

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 …

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

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 …

Normal Redefined: Exploring Decontextualization Of Lorises (Nycticebus & Xanthonycticebus Spp.) On Social Media Platforms, Luke F. Quarles, Kim Feddema, Marco Campera, K. A.I. Nekaris

Research outputs 2022 to 2026

Introduction: Decontextualization is a concept from psychology whereby new words are learned outside of the context of the here-and-now. Decontextualized language is used for discussing abstract concepts and is crucial to the development of academic language. When it comes to images, a dearth of context can lead to a lack of clarity, such as the use of ambiguous decontextualized images in environmental communication, leading to the promotion of greenwashing. Here we refer to decontextualization as the removal of wildlife from their wild ecological context. Images and videos of globally threatened species are increasingly popular on social media. Showing such taxa …

Global Online Trade In Primates For Pets, Vincent Nijman, Thais Q. Morcatty, Hani R. El Bizri, Hassan Al-Razi, Andie Ang, Ahmad Ardiansyah, Sadek Atoussi, Daniel Bergin, Sarah Bell, Franciany Braga-Pereira, Marco Campera, Nabajit Das, Felipe E. Silva, Kim Feddema, Grace Foreman, Anna Fourage, Smitha D. Gnanaolivu, Malene F. Hansen, Elena Račevska, Brittany C. Rapone, Ganga R. Regmi, Chris R. Shepherd, Sofiya Shukhova, Penthai Siriwat, Jaima H. Smith, Seyed A. M. M. Tabar, Aline S. Tavares, Ariana V. Weldon, Angelina Wilson, Nobuyuki Yamaguchi, Mingxia Zhang, Magdalena S. Svensson, K. Anne-Isola Nekaris

Research outputs 2022 to 2026

The trade in primates as pets is a global enterprise and as access to the Internet has increased, so too has the trade of live primates online. While quantifying primate trade in physical markets is relatively straightforward, limited insights have been made into trade via the Internet. Here we followed a three-pronged approach to estimate the prevalence and ease of purchasing primates online in countries with different socioeconomic characteristics. We first conducted a literature review, in which we found that Malaysia, Thailand, the USA, Ukraine, South Africa, and Russia stood out in terms of the number of primate individuals being …

Hate-Clipper: Multimodal Hateful Meme Classification Based On Cross-Modal Interaction Of Clip Features, Gokul Karthik Kumar, Karthik Nandakumar

Computer Vision Faculty Publications

Hateful memes are a growing menace on social media. While the image and its corresponding text in a meme are related, they do not necessarily convey the same meaning when viewed individually. Hence, detecting hateful memes requires careful consideration of both visual and textual information. Multimodal pretraining can be beneficial for this task because it effectively captures the relationship between the image and the text by representing them in a similar feature space. Furthermore, it is essential to model the interactions between the image and text features through intermediate fusion. Most existing methods either employ multimodal pre-training or intermediate fusion, …

A Comparative Analysis Of Anti-Vax Discourse On Twitter Before And After Covid-19 Onset, Tareq Nasralah, Ahmed El Noshokaty, Omar El-Gayar, Mohammad A. Al-Ramahi, Abdullah Wahbeh

Computer Information Systems Faculty Publications

This study aimed to identify and assess the prevalence of vaccine-hesitancy-related topics on Twitter in the periods before and after the Coronavirus Disease 2019 (COVID-19) outbreak. Using a search query, 272,780 tweets associated with anti-vaccine topics and posted between 1 January 2011, and 15 January 2021, were collected. The tweets were classified into a list of 11 topics and analyzed for trends during the periods before and after the onset of COVID-19. Since the beginning of COVID-19, the percentage of anti-vaccine tweets has increased for two topics, “government and politics” and “conspiracy theories,” and decreased for “developmental disabilities.” Compared to …

Using Deep Learning To Detect Social Media ‘Trolls’, Áine Macdermott, Michal Motylinski, Farkhund Iqbal, Kellyann Stamp, Mohammed Hussain, Andrew Marrington

All Works

Detecting criminal activity online is not a new concept but how it can occur is changing. Technology and the influx of social media applications and platforms has a vital part to play in this changing landscape. As such, we observe an increasing problem with cyber abuse and ‘trolling’/toxicity amongst social media platforms sharing stories, posts, memes sharing content. In this paper we present our work into the application of deep learning techniques for the detection of ‘trolls’ and toxic content shared on social media platforms. We propose a machine learning solution for the detection of toxic images based on embedded …

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 …

In A Digitally Connected World Through Likes, Hashtags And Followers - Advancing Surgical Research Through A Social Media: A Narrative Review, Sabah Uddin Saqib, Qamar` Riaz, Russell Seth Martins, Amna Riaz, Hasnain Zafar

Department for Educational Development

In this era of modern information technology, the world is now digitally connected through various platforms on social media, which has changed the way medical professionals work, communicate and learn. The use of social media in surgery is expanding, and it is now becoming an essential tool for surgical training, research and networking. Articles, journal clubs and surgical conferences are within reach of everyone regardless of geographical location worldwide. Electronic publications have now resoundingly replaced printed editions of journals. Collaborative research through social media platforms helps collect diverse data, enhancing the research's global generalisability. The current narrative review was planned …

The State Of Innovation And Media Viability In East Africa: From Indepth Media House Surveys, Hesbon Hansen Owilla, Rose Kimani, Ann Hollifield, Julia Wegner, Dennis Reineck, Roland Schürhoff

Graduate School of Media and Communications

Media houses globally are grappling with how best to produce quality content while at the same time remaining financially viable in the wake of shrinking revenues, technological disruptions, the emergence of peripheral content creators, competition for advertisement revenues from big tech platforms, the COVID-19 pandemic, and a myriad of other changes in the ecosystem. Despite these challenges, it is in the interest of the public that news media organisations (NMOs) produce quality content and do so in a financially sustainable fashion. Media viability, that is, producing quality journalism in a financially sustainable way, is, therefore, a growing area of focus. …

Does Active Service Intervention Drive More Complaints On Social Media? The Roles Of Service Quality And Awareness, Shujing Sun, Yang Gao, Huaxia Rui

Research Collection School Of Computing and Information Systems

Despite many advantages of social media as a customer service channel, there is a concern that active service intervention encourages excessive service complaints. Our paper casts doubt on this misconception by examining the dynamics between social media customer complaints and brand service interventions. We find service interventions indeed cause more complaints, yet this increase is driven by service awareness rather than chronic complaining. Due to the publicity and connectivity of social media, customers learn about the new service channel by observing customer service delivery to others – a mechanism that is unique to social media customer service and does not …

Tweets R Us: Predicting Personality From Language And Emoji Use On Twitter, Maxwell Meckling, Sarah Shoup, D. E. Chan-Tin, Shelia Kennison

Computer Science: Faculty Publications and Other Works

The research investigated the suggestion from prior research that language and emojis use on Twitter and other social media platforms can predict users’ personality and gender (Adali et al., 2014; Golbeck et al., 2011; Li et al., 2019; Moreno et al., 2019; Raess, 2018). Some studies have also analyzed Twitter language to identify individuals with specific health conditions (e.g., alcohol recovery, Golbeck, 2012; sleep problems, Suarez et al., 2018).

If strategies to predict Twitter users’ characteristics prove to be successful, future efforts to direct persuasive messages related to recommended practices in public health and/or cybersecurity will be possible. Commercial applications …

Themes, Communities And Influencers Of Online Probiotics Chatter: A Retrospective Analysis From 2009-2017, Santosh Vijaykumar, Aravind Sesagiri Raamkumar, Kristofor Mccarty, Cuthbert Mutumbwa, Jawwad Mustafa, Cyndy Au

Research Collection Lee Kong Chian School Of Business

We build on recent examinations questioning the quality of online information about probiotic products by studying the themes of content, detecting virtual communities and identifying key influencers in social media using data science techniques. We conducted topic modelling (n = 36,715 tweets) and longitudinal social network analysis (n = 17,834 tweets) of probiotic chatter on Twitter from 2009–17. We used Latent Dirichlet Allocation (LDA) to build the topic models and network analysis tool Gephi for building yearly graphs. We identified the top 10 topics of probiotics-related communication on Twitter and a constant rise in communication activity. However the number of …

Tourism-Related Climate Change Perspectives: Social Media Conversations About Canada’S Rocky Mountain National Parks, Farshid Mirzaalian, Elizabeth Halpenny

TTRA Canada 2021 Conference

This study employed quantitative social media big data analysis in conjunction with qualitative analysis of postings to better comprehend online lay discourse of climatic change issues in a nature-based tourism destination, Jasper National Park, Canada. Such mixed methodological approaches to big data enable tourism researchers to not only study unstructured social media big data for future-proofing purposes but to address some methodological concerns often raised about solely using corpus linguistic or thematic analyzes. This study unearthed divergent themes regarding tourists’ perceptions of climate change upon visiting JNP, with the most significant discourses on climate grief, education and interpretation, pro- environmental …

On Predicting Personal Values Of Social Media Users Using Community-Specific Language Features And Personal Value Correlation, Amila Silva, Pei Chi Lo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Personal values have significant influence on individuals’ behaviors, preferences, and decision making. It is therefore not a surprise that personal values of a person could influence his or her social media content and activities. Instead of getting users to complete personal value questionnaire, researchers have looked into a non-intrusive and highly scalable approach to predict personal values using user-generated social media data. Nevertheless, geographical differences in word usage and profile information are issues to be addressed when designing such prediction models. In this work, we focus on analyzing Singapore users’ personal values, and developing effective models to predict their personal …

More Kawaii Than A Real-Person Live Streamer: Understanding How The Otaku Community Engages With And Perceives Virtual Youtubers, Zhicong Lu, Chenxinran Shen, Jiannan Li, Hong Shen, Daniel Wigdor

Research Collection School Of Computing and Information Systems

Live streaming has become increasingly popular, with most streamers presenting their real-life appearance. However, Virtual YouTubers (VTubers), virtual 2D or 3D avatars that are voiced by humans, are emerging as live streamers and attracting a growing viewership in East Asia. Although prior research has found that many viewers seek real-life interpersonal interactions with real-person streamers, it is currently unknown what makes VTuber live streams engaging or how they are perceived differently than real-person streamers. We conducted an interview study to understand how viewers engage with VTubers and perceive the identities of the voice actors behind the avatars (i.e., Nakanohito). The …

Public Discourse Against Masks In The Covid-19 Era: Infodemiology Study Of Twitter Data, Mohammad A. Al-Ramahi, Ahmed El Noshokaty, Omar El-Gayar, Tareq Nasralah, Abdullah Wahbeh

Computer Information Systems Faculty Publications

Background:

Despite scientific evidence supporting the importance of wearing masks to curtail the spread of COVID-19, wearing masks has stirred up a significant debate particularly on social media.

Objective:

This study aimed to investigate the topics associated with the public discourse against wearing masks in the United States. We also studied the relationship between the anti-mask discourse on social media and the number of new COVID-19 cases.

Methods:

We collected a total of 51,170 English tweets between January 1, 2020, and October 27, 2020, by searching for hashtags against wearing masks. We used machine learning techniques to analyze the data …

Interplay Between Social Media Use, Sleep Quality, And Mental Health In Youth: A Systematic Review, Rea Alonzo, Junayd Hussain, Saverio Stranges, Kelly K. Anderson

Epidemiology and Biostatistics Publications

Social media applications are increasingly prominent among youth. This systematic review provides a comprehensive assessment of the literature on the relationship between active social media use, sleep quality, and common mental health outcomes (anxiety, depression, and psychological distress) among youth. MEDLINE, PsychINFO, EMBASE and Scopus were searched for observational studies investigating this relationship among youth (aged 16–25). Thirty-six cross-sectional studies and six prospective cohort studies met the inclusion criteria. Among cross-sectional studies, significant associations between excessive social media use with poor mental health outcomes (n = 33), poor sleep quality (n = 24), and significant associations between poor sleep quality …

Analyzing Tweets On New Norm: Work From Home During Covid-19 Outbreak, Swapna Gottipati, Kyong Jin Shim, Hui Hian Teo, Karthik Nityanand, Shreyansh Shivam

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic triggered a large-scale work-from-home trend globally in recent months. In this paper, we study the phenomenon of “work-from-home” (WFH) by performing social listening. We propose an analytics pipeline designed to crawl social media data and perform text mining analyzes on textual data from tweets scrapped based on hashtags related to WFH in COVID-19 situation. We apply text mining and NLP techniques to analyze the tweets for extracting the WFH themes and sentiments (positive and negative). Our Twitter theme analysis adds further value by summarizing the common key topics, allowing employers to gain more insights on areas of …