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Articles 1 - 9 of 9
Full-Text Articles in Computational Linguistics
Understanding Perceptions Of A Peruvian Local Market Program: A Reflexive Thematic Analysis, Rosmery Ramos-Sandoval Dr., Jano Ramos-Diaz
Understanding Perceptions Of A Peruvian Local Market Program: A Reflexive Thematic Analysis, Rosmery Ramos-Sandoval Dr., Jano Ramos-Diaz
The Qualitative Report
Despite growing global interest in short food supply chains (SFSCs), little is known about how consumers in developing countries perceive these models, especially through digital platforms like social media. This study investigates how Twitter users represent and perceive SFSCs in the context of the Peruvian government´s “De la Chacra a la Olla” program. The study analyzed 1,167 tweets from Peruvian Twitter users referencing the hashtag #DeLaChacraALaOlla between 2014 and 2020, using reflexive thematic analysis within an exploratory case study framework to examine consumer perceptions of SFSCs. The analysis revealed three key themes in consumer perceptions of SFSCs on Twitter: direct …
From Adversarial Attacks To Robust Classifiers - A Study In Social Media Spam Detection - Black Box & White Box, Jonathan Jose Penaloza Rumie
From Adversarial Attacks To Robust Classifiers - A Study In Social Media Spam Detection - Black Box & White Box, Jonathan Jose Penaloza Rumie
Undergraduate Theses
Adversarial attacks pose a significant threat to the reliability of machine learning-based spam detection systems in social media. This undergraduate thesis, "From Adversarial Attacks to Robust Classifiers: A Study in Social Media Spam Detection – Black Box & White Box," systematically examines the impact of both black-box and white-box adversarial attacks on a range of spam classifiers, including Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Bagging, Gradient Boosting, and Support Vector Machines. Leveraging a novel dataset derived from Twitter spam messages and enhanced with adversarial perturbations such as synonym replacement and character-level modifications, this study evaluates classifier performance under …
Characterizing Language Use In Online Accessibility Discussion Forums, Nithiya Venkatraman, Anand Ravi Aiyer, Yash Prakash, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok
Characterizing Language Use In Online Accessibility Discussion Forums, Nithiya Venkatraman, Anand Ravi Aiyer, Yash Prakash, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok
Computer Science Faculty Publications
Discussion forums are one of the favored platforms for knowledge sharing. Given their popularity, copious research exists on understanding the linguistic and behavioral characteristics of forum conversations, so as to inform the design of many downstream applications including discourse visualization, sentiment analysis, and question answering. However, prior investigations have mainly focused on general forums designed primarily for sighted users, and as such the applicability of their findings to dedicated accessibility discussion forums frequented by blind screen reader users remains unanswered. To bridge this knowledge gap and facilitate the development of better-informed assistive technologies for blind people, we investigated language use …
Technology In The Classroom: The Features Language Teachers Should Consider, Sophie Cuocci, Padideh Fattahi Marnani
Technology In The Classroom: The Features Language Teachers Should Consider, Sophie Cuocci, Padideh Fattahi Marnani
Journal of English Learner Education
The fast development of technology and the new generation of highly computer literate students led to consider the integration of technology in school as essential. Throughout the last two decades, research has identified multiple factors leading to the successful and unsuccessful integration of technology in the classroom. Educators must consider these factors when deciding on which technology tools to use and how to integrate them to their lessons. Simultaneously, the increasing number of English learners in the United States calls for the identification of teaching strategies that will best support their needs. Many language teachers now rely on teaching techniques …
Spectral Analysis Of Multiscale Cultural Traits On Twitter, Chandler Squires, Nikhil Kunapuli, Yaneer Bar-Yam, Alfredo Morales
Spectral Analysis Of Multiscale Cultural Traits On Twitter, Chandler Squires, Nikhil Kunapuli, Yaneer Bar-Yam, Alfredo Morales
Northeast Journal of Complex Systems (NEJCS)
Understanding and mapping the emergence and boundaries of cultural areas is a challenge for social sciences. In this paper, we present a method for analyzing the cultural composition of regions via Twitter hashtags. Cultures can be described as distinct combination of traits which we capture via principal component analysis (PCA). We investigate the top 8 PCA components of an area including France, Spain, and Portugal, in terms of the geographic distribution of their hashtag composition. We also discuss relationships between components and the insights those relationships can provide into the structure of a cultural space. Finally, we compare the spatial …
Misinformation And Disinformation: Detecting Fakes With The Eye And Ai, Victoria Rubin
Misinformation And Disinformation: Detecting Fakes With The Eye And Ai, Victoria Rubin
Data and Test Instruments
How do we detect, deter, and prevent the spread of mis- and disinformationwith the human eye and AI? How does theory inform the practice, and how do theevidence-based research and best practices in lie-catching and truth-seekingprofessions—inform AI? The book looks into well-established human practicessuch as the routines and processes used in detective work, journalism, and scientificinquiry, and how they contribute toward innovative AI solutions. The book explainsthe principles, inner workings, and recent evolution of five types of state-of-the-artAI technologies suitable for curtailing the spread of mis- and disinformation:automated deception detectors, clickbait detectors, satirical fake detectors, rumordebunkers, and computational fact-checking tools.
Latent Semantic Indexing In The Discovery Of Cyber-Bullying In Online Text, Jacob L. Bigelow
Latent Semantic Indexing In The Discovery Of Cyber-Bullying In Online Text, Jacob L. Bigelow
Computer Science Summer Fellows
The rise in the use of social media and particularly the rise of adolescent use has led to a new means of bullying. Cyber-bullying has proven consequential to youth internet users causing a need for a response. In order to effectively stop this problem we need a verified method of detecting cyber-bullying in online text; we aim to find that method. For this project we look at thirteen thousand labeled posts from Formspring and create a bank of words used in the posts. First the posts are cleaned up by taking out punctuation, normalizing emoticons, and removing high and low …
Detection Of Cyberbullying In Sms Messaging, Bryan W. Bradley
Detection Of Cyberbullying In Sms Messaging, Bryan W. Bradley
Computer Science Summer Fellows
Cyberbullying is a type of bullying that uses technology such as cell phones to harass or malign another person. To detect acts of cyberbullying, we are developing an algorithm that will detect cyberbullying in SMS (text) messages. Over 80,000 text messages have been collected by software installed on cell phones carried by participants in our study. This paper describes the development of the algorithm to detect cyberbullying messages, using the cell phone data collected previously. The algorithm works by first separating the messages into conversations in an automated way. The algorithm then analyzes the conversations and scores the severity and …
Cest: City Event Summarization Using Twitter, Deepa Mallela
Cest: City Event Summarization Using Twitter, Deepa Mallela
Computer Science Graduate Projects and Theses
Twitter, with 288 million active users, has become the most popular platform for continuous real-time discussions. This leads to huge amounts of information related to the real-world, which has attracted researchers from both academia and industry. Event detection on Twitter has gained attention as one of the most popular domains of interest within the research community. Unfortunately, existing event detection methodologies have yet to fully explore Twitter metadata and instead rely solely on identifying events based on prior information or focus on events that belong to specific categories. Given the heavy volume of tweets that discuss events, summarization techniques can …