Computer Engineering Commons^™

The Impact Of Social Media On Charitable Giving For Nonprofit Organization, Namchul Shin

Journal of International Technology and Information Management

Research has extensively studied nonprofit organizations’ use of social media for communications and interactions with supporters. However, there has been limited research examining the impact of social media on charitable giving. This research attempts to address the gap by empirically examining the relationship between the use of social media and charitable giving for nonprofit organizations. We employ a data set of the Nonprofit Times’ top 100 nonprofits ranked by total revenue for the empirical analysis. As measures for social media traction, i.e., how extensively nonprofits draw supporters on their social media sites, we use Facebook Likes, Twitter Followers, and Instagram …

Triggered By Socialbots: Communicative Anthropomorphization Of Bots In Online Conversations, Salla-Maaria Laaksonen, Kaisa Laitinen, Minna Koivula, Tanja Sihvonen

Human-Machine Communication

This article examines communicative anthropomorphization, that is, assigning of humanlike features, of socialbots in communication between humans and bots. Situated in the field of human-machine communication, the article asks how socialbots are devised as anthropomorphized communication companions and explores the ways in which human users anthropomorphize bots through communication. Through an analysis of two datasets of bots interacting with humans on social media, we find that bots are communicatively anthropomorphized by directly addressing them, assigning agency to them, drawing parallels between humans and bots, and assigning emotions and opinions to bots. We suggest that socialbots inherently have anthropomorphized characteristics and …

Classification Of Arabic Social Media Texts Based On A Deep Learning Multi-Tasks Model, Ali A. Jalil, Ahmed H. Aliwy

Al-Bahir Journal for Engineering and Pure Sciences

The proliferation of social networking sites and their user base has led to an exponential increase in the amount of data generated on a daily basis. Textual content is one type of data that is commonly found on these platforms, and it has been shown to have a significant impact on decision-making processes at the individual, group, and national levels. One of the most important and largest part of this data are the texts that express human intentions, feelings and condition. Understanding these texts is one of the biggest challenges that facing data analysis. It is the backbone for understanding …

Behind Derogatory Migrants' Terms For Venezuelan Migrants: Xenophobia And Sexism Identification With Twitter Data And Nlp, Joseph Martínez, Melissa Miller-Felton, Jose Padilla, Erika Frydenlund

Modeling, Simulation and Visualization Student Capstone Conference

The sudden arrival of many migrants can present new challenges for host communities and create negative attitudes that reflect that tension. In the case of Colombia, with the influx of over 2.5 million Venezuelan migrants, such tensions arose. Our research objective is to investigate how those sentiments arise in social media. We focused on monitoring derogatory terms for Venezuelans, specifically veneco and veneca. Using a dataset of 5.7 million tweets from Colombian users between 2015 and 2021, we determined the proportion of tweets containing those terms. We observed a high prevalence of xenophobic and defamatory language correlated with the …

Evaluation Of Different Machine Learning, Deep Learning And Text Processing Techniques For Hate Speech Detection, Nabil Shawkat

MSU Graduate Theses

Social media has become a domain that involves a lot of hate speech. Some users feel entitled to engage in abusive conversations by sending abusive messages, tweets, or photos to other users. It is critical to detect hate speech and prevent innocent users from becoming victims. In this study, I explore the effectiveness and performance of various machine learning methods employing text processing techniques to create a robust system for hate speech identification. I assess the performance of Naïve Bayes, Support Vector Machines, Decision Trees, Random Forests, Logistic Regression, and K Nearest Neighbors using three distinct datasets sourced from social …

Book Review: This Is How They Tell Me The World Ends: The Cyberweapons Arms Race (2020) By Nicole Perlroth, Amy C. Gaudion

Dickinson Law Review (2017-Present)

No abstract provided.

Analyzing Social Media Implementation In Hospitals In The U.S. Midwest Region, Dalsang Chung, C. Christopher Lee, David Hwang

Journal of International Technology and Information Management

The purpose of this research is to explore to what scale hospitals are adopting social media and implementing it in accordance with hospital characteristics. We reviewed hospitals’ social media activities on social networking sites such Facebook, Twitter, Instagram, and YouTube. We studied the 912 hospitals in the Midwest region reported in the 2015 American Hospital Association Annual Survey dataset. We reviewed each hospital’s social-networking page to understand the scale of social media adoption relative to the hospital’s characteristics such as bed count, state, ownership type (control), and specialty (service). We also considered whether the hospital is in a network and …

The Global Disinformation Order: 2019 Global Inventory Of Organised Social Media Manipulation, Samantha Bradshaw, Philip N. Howard

Copyright, Fair Use, Scholarly Communication, etc.

Executive Summary

Over the past three years, we have monitored the global organization of social media manipulation by governments and political parties. Our 2019 report analyses the trends of computational propaganda and the evolving tools, capacities, strategies, and resources.

1. Evidence of organized social media manipulation campaigns which have taken place in 70 countries, up from 48 countries in 2018 and 28 countries in 2017. In each country, there is at least one political party or government agency using social media to shape public attitudes domestically.

2.Social media has become co-opted by many authoritarian regimes. In 26 countries, computational propaganda …

An Analysis Of Rumor And Counter-Rumor Messages In Social Media, Dion Hoe-Lian Goh, Alton Y. K. Chua, Hanyu Shi, Wenju Wei, Haiyan Wang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Social media platforms are one of the fastest ways to disseminate information but they have also been used as a means to spread rumors. If left unchecked, rumors have serious consequences. Counter-rumors, messages used to refute rumors, are an important means of rumor curtailment. The objective of this paper is to examine the types of rumor and counter-rumor messages generated in Twitter in response to the falsely reported death of a politician, Lee Kuan Yew, who was Singapore’s first Prime Minister. Our content analysis of 4321Twitter tweets about Lee’s death revealed six categories of rumor messages, four categories ofcounter-rumor messages …

A Framework For Recommendation Of Highly Popular News Lacking Social Feedback, Nuno Moniz, Luís Torgo, Magdalini Eirinaki, Paula Branco

Faculty Publications

Social media is rapidly becoming the main source of news consumption for users, raising significant challenges to news aggregation and recommendation tasks. One of these challenges concerns the recommendation of very recent news. To tackle this problem, approaches to the prediction of news popularity have been proposed. In this paper, we study the task of predicting news popularity upon their publication, when social feedback is unavailable or scarce, and to use such predictions to produce news rankings. Unlike previous work, we focus on accurately predicting highly popular news. Such cases are rare, causing known issues for standard prediction models and …

An Unsupervised Multilingual Approach For Online Social Media Topic Identification, Siaw Ling Lo, Raymond Chiong, David Cornforth

Research Collection School Of Computing and Information Systems

Social media data can be valuable in many ways. However, the vast amount of content shared and the linguistic variants of languages used on social media are making it very challenging for high-value topics to be identified. In this paper, we present an unsupervised multilingual approach for identifying highly relevant terms and topics from the mass of social media data. This approach combines term ranking, localised language analysis, unsupervised topic clustering and multilingual sentiment analysis to extract prominent topics through analysis of Twitter’s tweets from a period of time. It is observed that each of the ranking methods tested has …

Communication Through Social Technologies: A Study Of Israeli Women, Jeretta Horn Nord 405-747-0320, Dafni Biran Achituv, Joanna Paliszkiewicz

Journal of International Technology and Information Management

Social technologies have changed the way we communicate allowing users to interact, share knowledge, reach out to friends and family, keep up with the news, and even promote and support a business. A study of Israeli women was conducted to determine how social technologies platforms — Facebook, Twitter, LinkedIn, YouTube, and Google+ — are used and the benefits realized. Women worldwide face challenges including economic, educational, health, and political. Israel women, like women in every other country in the world, are challenged with gender inequity. Do women who use social technologies believe that these platforms provide empowerment leading to greater …

How We Got Here: Connectivity, Creativity, Confluence And Internet Culture, Tziporah Stern, Linda Wieser Friedman, Hershey H. Friedman

Journal of International Technology and Information Management

There are more innovations today than at any time in human history. The companies that value creativity and diversity of ideas in their hires are the ones most likely to thrive. Indeed, the key asset of a corporation is the abilities, innovativeness, and creativity of its employees. The authors construct a timeline of critical events leading up to today’s highly networked and interconnected world with its ubiquitous social media technologies. The current state has been influenced by advances in media, technology, military defense, and commerce. One trend that stands out in this timeline is the increasing rate of change. It …

Content Mining Techniques For Detecting Cyberbullying In Social Media, Shawniece L. Parker, Yen-Hung Hu

Virginia Journal of Science

The use of social media has become an increasingly popular trend, and it is most favorite amongst teenagers. A major problem concerning teens using social media is that they are often unaware of the dangers involved when using these media. Also, teenagers are more inclined to misuse social media because they are often unaware of the privacy rights associated with the use of that particular media, or the rights of the other users. As a result, cyberbullying cases have a steady rise in recent years and have gone undiscovered, or are not discovered until serious harm has been caused to …

Detecting, Modeling, And Predicting User Temporal Intention, Hany M. Salaheldeen

Computer Science Theses & Dissertations

The content of social media has grown exponentially in the recent years and its role has evolved from narrating life events to actually shaping them. Unfortunately, content posted and shared in social networks is vulnerable and prone to loss or change, rendering the context associated with it (a tweet, post, status, or others) meaningless. There is an inherent value in maintaining the consistency of such social records as in some cases they take over the task of being the first draft of history as collections of these social posts narrate the pulse of the street during historic events, protest, riots, …

Developing A Conceptual Framework For Modeling Deviant Cyber Flash Mob: A Socio-Computational Approach Leveraging Hypergraph Constructs, Samer Al-Khateeb, Nitin Agarwal

Journal of Digital Forensics, Security and Law

In a Flash Mob (FM) a group of people get together in the physical world perform an unpredicted act and disperse quickly. Cyber Flash Mob (CFM) is the cyber manifestation of flash mob coordinated primarily using social media. Deviant Cyber Flash Mob (or, DCFM) is a special case of CFM, which is categorized as the new face of transnational crime organizations (TCOs). The DCFM phenomenon can be considered as a form of a cyber-collective action that is defined as an action aiming to improve group’s conditions (such as, status or power). In this paper, we conduct a conceptual analysis of …

Attitudes And Behaviors In Online Communities: Empirical Studies Of The Effects Of Social, Community, And Individual Characteristics, Richard Kumi

Graduate Theses and Dissertations

Online communities and communities of practice bring people together to promote and support shared goals and exchange information. Personal interactions are important to many of these communities and one of the important outcomes of personal interactions in online communities and communities of practice is user-generated content. The three essays in the current study examines behavior motivation in online communities and communities of practice to understand how Social and personal psychological factors, and user-generated influence attitudes, intentions and behaviors in online communities.

The first essay addresses two research questions. First, how does Social capital influence exchange and combination behaviors in online …

When Antitrust Met Facebook, Christopher S. Yoo

All Faculty Scholarship

Social networks are among the hottest phenomena on the Internet. Facebook eclipsed Google as the most visited website in both 2010 and 2011. Moreover, according to Nielsen estimates, as of the end of 2011 the average American spent nearly seven hours per month on Facebook, which is more time than they spent on Google, Yahoo!, YouTube, Microsoft, and Wikipedia combined. LinkedIn’s May 19, 2011 initial public offering (“IPO”) surpassed expectations, placing the value of the company at nearly $9 billion, and approximately a year later, its stock price had risen another 20 percent. Facebook followed suit a year later with …

Using Textual Features To Predict Popular Content On Digg, Paul H. Miller

Paul H Miller

Over the past few years, collaborative rating sites, such as Netflix, Digg and Stumble, have become increasingly prevalent sites for users to find trending content. I used various data mining techniques to study Digg, a social news site, to examine the influence of content on popularity. What influence does content have on popularity, and what influence does content have on users’ decisions? Overwhelmingly, prior studies have consistently shown that predicting popularity based on content is difficult and maybe even inherently impossible. The same submission can have multiple outcomes and content neither determines popularity, nor individual user decisions. My results show …

Using Textual Features To Predict Popular Content On Digg, Paul H. Miller

Department of English: Dissertations, Theses, and Student Research

Over the past few years, collaborative rating sites, such as Netflix, Digg and Stumble, have become increasingly prevalent sites for users to find trending content. I used various data mining techniques to study Digg, a social news site, to examine the influence of content on popularity. What influence does content have on popularity, and what influence does content have on users’ decisions? Overwhelmingly, prior studies have consistently shown that predicting popularity based on content is difficult and maybe even inherently impossible. The same submission can have multiple outcomes and content neither determines popularity, nor individual user decisions. My results show …

Infoextractor – A Tool For Social Media Data Mining, Chirag Shah, Charles File

JITP 2011: The Future of Computational Social Science

We present InfoExtractor, a web-based tool for collecting data and metadata from focused social media content. InfoExtractor then provides this data in various structured and unstructured formats for easy manipulation and analysis. The tool allows social science researchers to easily collect data for quantitative analysis, and is designed to deliver data from popular and influential social media sites in a useful and easy to access way. InfoExtractor was designed to replace traditional means of content aggregation, such as page scraping and brute- force copying.