Computer Engineering Commons^™

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 …

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 …

Data Analysis Through Social Media According To The Classified Crime, Serkan Savaş, Nuretti̇n Topaloğlu

Turkish Journal of Electrical Engineering and Computer Sciences

The amount and variety of data generated through social media sites has increased along with the widespread use of social media sites. In addition, the data production rate has increased in the same way. The inclusion of personal information within these data makes it important to process the data and reach meaningful information within it. This process can be called intelligence and this meaningful information may be for commercial, academic, or security purposes. An example application is developed in this study for intelligence on Twitter. Crimes in Turkey are classified according to Turkish Statistical Institute criminal data and keywords are …

A Hybrid Sentiment Analysis Method For Turkish, Buket Erşahi̇n, Özlem Aktaş, Deni̇z Kilinç, Mustafa Erşahi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a hybrid methodology for Turkish sentiment analysis, which combines the lexicon-based and machine learning (ML)-based approaches. On the lexicon-based side, we use a sentiment dictionary that is extended with a synonyms lexicon. Besides this, we tackle the classification problem with three supervised classifiers, naive Bayes, support vector machines, and J48, on the ML side. Our hybrid methodology combines these two approaches by generating a new lexicon-based value according to our feature generation algorithm and feeds it as one of the features to machine learning classifiers. Despite the linguistic challenges caused by the morphological structure of Turkish, the …

Refugees' Social Media Activities In Turkey: A Computational Analysis And Demonstration Method, Muhammed Abdullah Bülbül, Salah Haj Ismail

Turkish Journal of Electrical Engineering and Computer Sciences

This study performs a data analysis on refugees in Turkey based on their social media activities. In order to achieve this, we first propose a method to find their relevant public accounts and collect their activities generating a dataset. Then, we perform spatial and temporal analysis over this dataset to shed light on the most important topics and events discussed in social networks. We present the results graphically for ease of understanding and comparison. Our results indicate that we can reveal the most shared topics over a specific time and place as well as the change of pattern in refugees' …

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 …

Data-Driven And Knowledge-Based Strategies For Realizing Crowd Wisdom On Social Media, Shreyansh Bhatt

Browse all Theses and Dissertations

The wisdom of the crowd is a well-known example of collective intelligence wherein an aggregated judgment of a group of individuals is superior to that of an individual. The aggregated judgment is surprisingly accurate for predicting the outcome of a range of tasks from geopolitical forecasting to the stock price prediction. Recent research has shown that participants' previous performance data contributes to the identification of a subset of participants that can collectively predict an accurate outcome. In the absence of such performance data, researchers have explored the role of human-perceived diversity, i.e., whether a human considers a crowd as a …

Content-Based Clustering And Visualization Of Social Media Text Messages, Sydney A. Barnard

Browse all Theses and Dissertations

Although Twitter has been around for more than ten years, crisis management agencies and first response personnel are not able to fully use the information this type of data provides during a crisis or natural disaster. This thesis addresses clustering and visualizing social media data by textual similarity, rather than by only time and location, as a tool for first responders. This thesis presents a tool that automatically clusters geotagged text data based on their content and displays the clusters and their locations on the map. It allows at-a-glance information to be displayed throughout the evolution of a crisis. For …

A Semantically Enhanced Approach To Identify Depression-Indicative Symptoms Using Twitter Data, Ankita Saxena

Browse all Theses and Dissertations

According to the World Health Organization, more than 300 million people suffer from Major Depressive Disorder (MDD) worldwide. PHQ-9 is used to screen and diagnose MDD clinically and identify its severity. With the unprecedented growth and enthusiastic acceptance of social media such as Twitter, a large number of people have come to share their feelings and emotions on it openly. Each tweet can indicate a user's opinion, thought or feeling. A tweet can also indicate multiple symptoms related to PHQ-9. Identifying PHQ-9 symptoms indicated by a tweet can provide crucial information about a user regarding his/her depression diagnosis. The current …

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 …

Web-Based Interactive Social Media Visual Analytics, Diego Rodríguez-Baquero, Jiawei Zhang, David S. Ebert, Sorin A. Matei

The Summer Undergraduate Research Fellowship (SURF) Symposium

Real-time social media platforms enable quick information broadcasting and response during disasters and emergencies. Analyzing the massive amount of generated data to understand the human behavior requires data collection and acquisition, parsing, filtering, augmentation, processing, and representation. Visual analytics approaches allow decision makers to observe trends and abnormalities, correlate them with other variables and gain invaluable insight into these situations. In this paper, we propose a set of visual analytic tools for analyzing and understanding real-time social media data in times of crisis and emergency situations. First, we model the degree of risk of individuals’ movement based on evacuation zones …

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, …

Non-Learning Semantic Analysis For Context Discovery And Sentiment Estimation: Transportation Application, Himanshu Verma

UNLV Theses, Dissertations, Professional Papers, and Capstones

With enormous amount of linguistic data present on web, text analysis has become one of the major fields of interest today. This field includes sentiment analysis, information retrieval, text document classification, knowledge based modeling, content similarity measure, data clustering, words prediction/correction, decision making etc. Managing and processing such data has vital importance. The field being quite broad, our focus is mainly on transportation related social media(Twitter) data extraction, text categorization/classification which can be further sub-divided into concept discovery, word sense disambiguation and sentiment analysis to analyze performance of existing transportation system worldwide. Concept discovery is the method of extracting the …

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 …

Locational Wireless And Social Media-Based Surveillance, Maxim Chernyshev

Australian Digital Forensics Conference

The number of smartphones and tablets as well as the volume of traffic generated by these devices has been growing constantly over the past decade and this growth is predicted to continue at an increasing rate over the next five years. Numerous native features built into contemporary smart devices enable highly accurate digital fingerprinting techniques. Furthermore, software developers have been taking advantage of locational capabilities of these devices by building applications and social media services that enable convenient sharing of information tied to geographical locations. Mass online sharing resulted in a large volume of locational and personal data being publicly …

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 …