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Full-Text Articles in Engineering
Triggered By Socialbots: Communicative Anthropomorphization Of Bots In Online Conversations, Salla-Maaria Laaksonen, Kaisa Laitinen, Minna Koivula, Tanja Sihvonen
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
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
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
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 …