Social Media Commons^™

Angrybert: Joint Learning Target And Emotion For Hate Speech Detection, Md Rabiul Awal, Rui Cao, Roy Ka-Wei Lee, Sandra Mitrović

Research Collection School Of Computing and Information Systems

Automated hate speech detection in social media is a challenging task that has recently gained significant traction in the data mining and Natural Language Processing community. However, most of the existing methods adopt a supervised approach that depended heavily on the annotated hate speech datasets, which are imbalanced and often lack training samples for hateful content. This paper addresses the research gaps by proposing a novel multitask learning-based model, AngryBERT, which jointly learns hate speech detection with sentiment classification and target identification as secondary relevant tasks. We conduct extensive experiments to augment three commonly-used hate speech detection datasets. Our experiment …

Escape From An Echo Chamber, Kuan-Chieh Lo, Shih-Chieh Dai, Aiping Xiong, Jing Jiang, Lun-Wei Ku

Research Collection School Of Computing and Information Systems

An echo chamber effect refers to the phenomena that online users revealed selective exposure and ideological segregation on political issues. Prior studies indicate the connection between the spread of misinformation and online echo chambers. In this paper, to help users escape from an echo chamber, we propose a novel news-analysis platform that provides a panoramic view of stances towards a particular event from different news media sources. Moreover, to help users better recognize the stances of news sources which published these news articles, we adopt a news stance classification model to categorize their stances into “agree”, “disagree”, “discuss”, or “unrelated” …

J Mich Dent Assoc April 2021

The Journal of the Michigan Dental Association

In the April 2021 issue of the Journal of the Michigan Dental Association, we offer a comprehensive range of original feature content showcasing the latest developments in dental practice and knowledge, including:

1. AI in Dental Care Delivery: Explore the groundbreaking role of Artificial Intelligence (AI) and Machine Learning in dental care, revolutionizing efficiency, safety, care outcomes, and treatment planning consistency.
2. AI in Dental Claims Processing: Discover how AI is employed by third-party payers to streamline dental claims processing, resulting in cost containment and the proactive identification of potential fraud, waste, and abuse.
3. Evidence-Based Dentistry: As part of …

Social Media User Relationship Framework (Smurf), Anne David, Sarah Morris, Gareth Appleby-Thomas

Journal of Digital Forensics, Security and Law

The use of social media has spread through many aspects of society, allowing millions of individuals, corporate as well as government entities to leverage the opportunities it affords. These opportunities often end up being exploited by a small percentage of the user community who use it for objectionable or unlawful activities; for example, trolling, cyber bullying, grooming, luring. In some cases, these unlawful activities result in investigations where swift retrieval of critical evidence required in order to save a life.

This paper presents a proof of concept (PoC) framework for social media user attribution. The framework aims to provide digital …

Image Source Identification Using Convolutional Neural Networks In Iot Environment, Yan Wang, Qindong Sun, Dongzhu Rong, Shancang Li, Li Da Xu

Information Technology & Decision Sciences Faculty Publications

Digital image forensics is a key branch of digital forensics that based on forensic analysis of image authenticity and image content. The advances in new techniques, such as smart devices, Internet of Things (IoT), artificial images, and social networks, make forensic image analysis play an increasing role in a wide range of criminal case investigation. This work focuses on image source identification by analysing both the fingerprints of digital devices and images in IoT environment. A new convolutional neural network (CNN) method is proposed to identify the source devices that token an image in social IoT environment. The experimental results …

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 …

Chronic Customers Or Increased Awareness? The Dynamics Of Social Media Customer Service, Shujing Sun, Yang Gao, Huaxia Rui

Research Collection School Of Computing and Information Systems

Despite that social media has become a promising alternative to traditional call centers, managers hesitate to fully harness its power because they worry that active service intervention may encourage excessive use of the channel by disgruntled customers. This paper sheds light on such a concern by examining the dynamics between brand-level customer complaints and service interventions on social media. Using details of customer-brand interactions of 40 airlines on Twitter, we find that more service interventions indeed cause more customer complaints, accounting for the online customer population and service quality. However, the increased complaints are primarily driven by the awareness enhancement …

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 …

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 …

Narrowing The Wealth And Income Gap In Poland, China, And The United States, Cyndy Carboo, Zhiling Song, Jiawei Feng, Xudong Zhu

School of Professional Studies

With the widespread of globalization, the wealth gap continues to widen globally. Due to the enormous differences in national conditions and political systems of various countries, this article selects China, the United States, and Poland as the research objects, and uses a specific time unit as the benchmark, and mainly focuses on the four directions of medical care, education, job opportunities, and pensions. A reader could understand the correlation between the wealth gap and multiple factors deeply in this article. This article analyzes the impact of income disparity on these three countries and proposes solutions to help narrow the gap …

Worst Time Being Poor? The Hunger Problem In U.S. During Covid-19 Pandemic, Yuanhang Hu

School of Professional Studies

Food insecurity is deeply rooted in American society during and before the COVID-19 pandemic. Food Insecurity usually associates with economic indicators, such as unemployment rate, income level, etc. Currently, there are two main tools to fight the war of hunger. The first one is the government food assistance programs. And the second one is food pantries from the private sectors of the community. Both tools are facing numerous challenges due to COVID-19. The purpose of this article is to provide rational reasons to persuade the government to enhance the benefits of the Supplemental Nutrition Assistance Program (SNAP) and use administrative …

The Practical Applications Of Video Games Beyond Entertainment, Jack Martin

School of Professional Studies

Much of the attention directed toward video games is focused on their role as entertainment. However, researchers have found that video games can have other, more practical uses for society. This thesis is designed to examine three specific examples of the practical applications of video games: video games in education, video games as accessible technology, and the social uses of video games. This project is based on pre-existing research conducted by professionals studying the aforementioned subtopics. Anecdotal stories from educators, people with disabilities, and developers are also discussed. The thesis explores specific examples of video games being used practically, and …

Transparency And Yielding Of Law Officers Reform (Taylor) Act Of 2020: Proposal For Police Reform, Marwa Alnaal, Matthew L. Anderson, Hannah Brier, Mollie Campbell, Rose Wine

School of Professional Studies

The Transparency and Yielding of Law Officers Reform Act of 2020 (TAYLOR) proposes an example bill for law enforcement reform. During the summer of 2020, the United States witnessed civilian demonstrations nationwide calling for a change to policing. Our proposal is hoping to heed that call, offering a foundation for change that police forces and localities across the United States can utilize to rebuild trust and accountability.

The goal of the TAYLOR Act is not to defund the police; but rather, TAYLOR rethinks the priorities of the police. There can be no denying that the relationship of trust and security …

How Museum Utilize Social Media On Communication, Jiake Han

School of Professional Studies

With the development of Internet, social media became more and more popular among people. Many industries realize the importance of social media in business. Traditionally, museum concentrates more on personal visual experience, which is hard to be replaced by online media. However, museums now also put more concentrate on social media platform because it expands the way of engagement. Especially, for Coronavirus, many organizations including museums have to close. Therefore, museums have to depend more on social media platforms to communicate with audiences. This research aims at finding how different kind of social media help museum communicate and engage with …

Healthy Food Portal Business Plan And Its Function Model, Alena Raupova

School of Professional Studies

Business planning is a tool of paramount importance in the process of company management, on the efficiency of which the future functioning of the enterprise depends. Formation of a business plan enables the team to productively and competently use existing funds and resources in their work and apply planning as a very effective management mechanism (Hamm, 2016).

The goal of this final project is to develop a business plan for a healthy nutrition portal for Bellyful LLC. Bellyful is based in Boston, USA, and the portal will be its first product. Our client is interested in researching the prospects of …

A Web-Based Ai Assistant Application Using Python And Javascript, Viet Le, Tej Bahadur, Jainee Shah, Roushan Ara

School of Professional Studies

Our research is mainly based on a chatbot which is powered by Artificial Intelligence. Nowadays, Artificial Intelligence assistants such as Apple’s Siri, Google’s Now and Amazon’s Alexa are currently fast-growing and widely integrated with many smart devices. These assistants are built with the primary purpose of being personal assistants for every individual user in certain contexts. In this research, we would highlight the development process of the chatbots, features, problems, case studies and limitations.

This research delivers the information, helps developers to build answer bots and integrate chatbots with business accounts. The aim is to assist users and allow transactions …

Rcap Solutions Breach Management - Case Study, Eugene Adu-Gyamfi, Gio Al Muarrawi, Kwame Ofori

School of Professional Studies

Companies get hacked every day, and our in-scope company for this case study, RCAP Solution, was not an exception. Security incidents have increased both in volume and range in recent years, and cyber-attacks have become more sophisticated than ever before. There are so many reasons that drive this fact; one is that our infrastructure was not protected efficiently, but also attackers have become more knowledgeable in initiating advanced attacks at a scale. Additionally, the entrance of emerging technologies such as blockchain, machine learning, and the internet of things, added additional complexity to the already complex scene. Cybercriminals are using various …

Cvs Covid-19 Screening Website: Test Automation, Savya Rawat

School of Professional Studies

CVS Pharmacy is an American retail corporation, also known as, and originally named, the Consumer Value Store owned by CVS Health, it is headquartered in Woonsocket, Rhode Island. CVS Pharmacy is currently the largest pharmacy chain in the United States by number of locations over 9,600 and total prescription revenue. CVS sells prescription drugs and a wide assortment of general merchandise, including over-the-counter drugs.

Now, coming to the reason why I have selected CVS pharmacy’s website cvs.com as my case study topic is because of CVS’s response to the covid-19 pandemic’s no-cost testing strategy. Whole of the world is suffering …

The Impact Of Special Interest Groups On The Federal Dietary Guidelines: Consequences For American Health, Dory Mcmillan

School of Professional Studies

This research paper explores the impact of relationships between lobbyists and both the USDA and HSS, and the impact these relationships have on the Dietary Guidelines for Americans that the agencies work together to create. The paper focuses specifically on the information the guidelines present in regard to red meat consumption, and the impacts this may have on American health, and healthcare costs associated. It was hypothesized that a relationship would be found between special interest groups and the U.S. Department of Health and Human Services and/or the U.S. Department of Agriculture. Research found there was a relationship between special …

The Killingly Mascot Case Study, Jordan Lumpkins

School of Professional Studies

In the summer of 2019, in Killingly, Connecticut the local Board of Education voted to retire the "Redmen" mascot name it had used for nearly a century. This legislation was widely opposed and received extensive media coverage. Within a few months, the town experienced a massive political referendum where several local Board of Education members and Councilmen were replaced by single issue politicians promising to reinstate the "Redmen" name. Now holding a majority on the Board of Education, these Board members made Killingly the first school in U.S. history to reinstate a mascot after being deemed "derogatory."

It is the …

Higher Education Responses To Crisis: A Case Study Of Clark University And The Pandemic Of 2020, Lisa Gillingham

School of Professional Studies

The COVID-19 pandemic has delivered an existential challenge to universities and other academic institutions at a time when they are already grappling with other weighty issues that may alter the fabric of higher education. COVID-19 has forced these institutions to consider and employ new ways of conducting its work with a sense urgency that is unprecedented in the recent history of the academy. The rate of learning around these models is rapid, and Higher Education is ripe for change.

Clark University has addressed the pandemic with a plan to protect and pivot using strategies that support the continuation of its …

Argumentation Stance Polarity And Intensity Prediction And Its Application For Argumentation Polarization Modeling And Diverse Social Connection Recommendation, Joseph Winstead Sirrianni

Graduate Theses and Dissertations

Cyber argumentation platforms implement theoretical argumentation structures that promote higher quality argumentation and allow for informative analysis of the discussions. Dr. Liu’s research group has designed and implemented a unique platform called the Intelligent Cyber Argumentation System (ICAS). ICAS structures its discussions into a weighted cyber argumentation graph, which describes the relationships between the different users, their posts in a discussion, the discussion topic, and the various subtopics in a discussion. This platform is unique as it encodes online discussions into weighted cyber argumentation graphs based on the user’s stances toward one another’s arguments and ideas. The resulting weighted cyber …

Adelaidecyc At Semeval-2020 Task 12: Ensemble Of Classifiers For Offensive Language Detection In Social Media, Mahen Herath, Thushari Atapattu, Hoang Anh Dung, Christoph Treude, Katrina Falkner

Research Collection School Of Computing and Information Systems

This paper describes the systems our team (AdelaideCyC) has developed for SemEval Task 12 (OffensEval 2020) to detect offensive language in social media. The challenge focuses on three subtasks – offensive language identification (subtask A), offense type identification (subtask B), and offense target identification (subtask C). Our team has participated in all the three subtasks. We have developed machine learning and deep learning-based ensembles of models. We have achieved F1-scores of 0.906, 0.552, and 0.623 in subtask A, B, and C respectively. While our performance scores are promising for subtask A, the results demonstrate that subtask B and C still …

Identifying And Characterizing Alternative News Media On Facebook, Samuel S. Guimaraes, Julia C. S. Reis, Lucas Lima, Filipe N. Ribeiro, Marisa Vasconcelos, Jisun An, Haewoon Kwak, Fabricio Benevenuto

Research Collection School Of Computing and Information Systems

As Internet users increasingly rely on social media sites to receive news, they are faced with a bewildering number of news media choices. For example, thousands of Facebook pages today are registered and categorized as some form of news media outlets. This situation boosted the so-called independent journalism, also known as alternative news media. Identifying and characterizing all the news pages that play an important role in news dissemination is key for understanding the news ecosystems of a country. In this work, we propose a graph-based semi-supervised method to measure the political bias of pages on most countries and show …

Digital Social Listening On Conversations About Sexual Harassment, Xuesi Sim, Ern Rae Chang, Yu Xiang Ong, Jie Ying Yeo, Christine Bai Shuang Yan, Eugene Wen Jia Choy, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

In light of the #MeToo movement and publicized sexual harassment incidents in Singapore in recent years, we built an analytics pipeline for performing digital social listening on conversations about sexual harassment for AWARE (Association of Women for Action and Research). Our social network analysis results identified key influencers that AWARE can engage for sexual harassment awareness campaigns. Further, our analysis results suggest new hashtags that AWARE can use to run social media campaigns and achieve greater reach.

Social Media Analytics: A Case Study Of Singapore General Election 2020, Sebastian Zhi Tao Khoo, Leong Hock Ho, Ee Hong Lee, Danston Kheng Boon Goh, Zehao Zhang, Swee Hong Ng, Haodi Qi, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

The 2020 Singaporean General Election (GE2020) was a general election held in Singapore on July 10, 2020. In this study, we present an analysis on social conversations about GE2020 during the election period. We analyzed social conversations from popular platforms such as Twitter, HardwareZone, and TR Emeritus.

Business Practice Of Social Media - Platform And Customer Service Adoption, Shujing Sun, Yang Gao, Huaxia Rui

Research Collection School Of Computing and Information Systems

This paper examines the key drivers in business adoptions of the platform and customer service within the context of social media. We carry out the empirical analyses using the decision trajectories of the international airline industry on Twitter. We find that a firm's decision-making is subject to both peer influence and consumer pressure. Regarding peer influence, we find that the odds of both adoptions increase when the extent of peers' adoption increases. We also identify the distinctive role of consumers. Specifically, before the platform adoption, firms learn about potential consequences from consumer reactions to peers' adoptions. Upon the platform adoption, …

Coupled Hierarchical Transformer For Stance-Aware Rumor Verification In Social Media Conversations, Jianfei Yu, Jing Jiang, Ling Min Serena Khoo, Hai Leong Chieu, Rui Xia

Research Collection School Of Computing and Information Systems

The prevalent use of social media enables rapid spread of rumors on a massive scale, which leads to the emerging need of automatic rumor verification (RV). A number of previous studies focus on leveraging stance classification to enhance RV with multi-task learning (MTL) methods. However, most of these methods failed to employ pre-trained contextualized embeddings such as BERT, and did not exploit inter-task dependencies by using predicted stance labels to improve the RV task. Therefore, in this paper, to extend BERT to obtain thread representations, we first propose a Hierarchical Transformer1 , which divides each long thread into shorter subthreads, …

A Tripartite Model Of Trust In Facebook: Acceptance Of Information Personalization, Privacy Concern, And Privacy Literacy, Sonny Rosenthal, Ole-Christian Wasenden, Gorm-Andreas Gronnevet, Rich Ling

Research Collection College of Integrative Studies

This study draws on the mental accounting perspective and a tripartite model of trust to explain why users trust Facebook. We argue that trust in Facebook is related to (1) trust in companies that collect personal data, (2) acceptance of information personalization, (3) low privacy concern, and (4) low privacy literacy. Further, we argue that privacy literacy amplifies the relationship between privacy concern and the other factors. This is because, among individuals with high privacy literacy, privacy concern is especially diagnostic of the potential harms of a loss of privacy. These arguments align broadly with theorizations about factors influencing privacy-related …

We Mind Your Well-Being: Preventing Depression In Uncertain Social Networks By Sequential Interventions, Aye Phye Phye Aung, Xinrun Wang, Bo An, Xiaoli Li

Research Collection School Of Computing and Information Systems

Mental health has become a major concern according to WHO who estimates that more than 350 million people worldwide are affected by depression. Studies have shown that interventions and social support can reduce stress and depression. However, counselling centers do not have enough resources to provide counselling and social support to all the participants in their interest. This paper helps social support organizations (e.g., university counselling centers) sequentially select the participants for interventions. Unfortunately, previous works do not consider emotion propagation from other neighbours of the influencees and initial uncertainties of mental states and influence. Moreover, they fail to scale …