scholarly journals Verbal Aggression on Social Media: How, why and its Automatic Identification

2021 ◽  
Author(s):  
Ritesh Kumar
Keyword(s):  
Social Media ◽  
Quantitative Study ◽  
Large Scale ◽  
User Study ◽  
Hate Speech ◽  
Verbal Aggression ◽  
User Studies ◽  
Automatic Identification ◽  
System P ◽  
Overall Performance

In recent times, verbal aggression and related phenomena of hate speech, abusive language, trolling, etc. have become a major problem over social media. In this paper, I present the results of a large-scale quantitative study of aggression based on a target-based typology in a manually-annotated multilingual dataset of over 20,000 Facebook comments and tweets each written in Hindi, English or code-mixed Hindi-English. Taking insights from this study, I develop 2 different classifiers for detecting aggression in Hindi, English and Hindi-English mixed Facebook and Twitter conversations. The classifiers are developed using an annotatedcorpus of approximately 9,000 Facebook comments and 5,000 tweets. Since a phenomenon like aggression is highly subjective, the study shows a comparatively modest inter-annotator agreement of 0.72 and an overall F1 score of 0.64 for both Facebook and Twitter. Consequently, I also carried out two user studies, where humans were asked to evaluate the annotations by the classifier, to test the actual 'acceptance' of the classifier's judgments. I discuss the results of this user study and give an analysis of the overall performance of the system.

scholarly journals Hate Speeches on Twitter and Facebook in South Asia: A Case Study Of Malala Yousufzai

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Saba Naz, Dr. Muhammad Osama Shafiq
Keyword(s):  
Social Media ◽  
South Asia ◽  
Quantitative Research ◽  
Large Scale ◽  
Hate Speech ◽  
Radical Change ◽  
Quantitative Research Methods ◽  
Social Media Platforms ◽  
Media Platform

Nowadays social media platforms have become a medium that allows people to post anything they wish. Since the time internet grew, a radical change has been discerned in society. With the emergence of social media sites, many challenges also thrived in the society that took the society into interesting and alarming ways altogether. As time is passing as technology is intensifying new forms of hate, abuse, bullying, and discrimination are also increasing in society. It can be said that digital technology is reshaping coercion based on caste, color, gender, race, culture, likes, dislikes. Many societies are concerned with this problem of growing hate speeches on social media but no proper barrier on these sites has been seen to prevent hate discourses. This study examined the attitudes of social media users including Facebook and Twitter over the incident of Noble Prize laureate Malala Yousufzai, a young activist who worked and spoke for the educational rights of girls who were born in Swat valley. She spoke against this erroneous system that didn’t allow girls to gain education and became a prominent member of society at the little age of 14. She was shot by Taliban and then a controversy started against her, some people admired her and she became a celebrity all over South Asia while an extreme amount of criticism was also seen against her incident. Through this study, we aim to understand the abundance of hate speech on Facebook and Twitter in South Asia by using Qualitative and Quantitative Research Methods. For that purpose we took the case study method and provide a large-scale measurement and analysis of different hashtags used during the case of Malala on the social media platform. To achieve the objective of our research, we amassed Tweets and Facebook posts posted since the year 2011 till now related to this case. This article identifies numerous forms of hate speeches on social media that are arising in South Asia and altering the minds of people using social media, it is also guiding how to abate hate speeches that are delivered on social media with particular hashtags on various incidents and matters. The collected data revealed that hate speech has become a social problem with substantial inimical effects in societies. This study explains that social media should be utilized to benefit mankind positively and gently.

scholarly journals Natural Language Model for Automatic Identification of Intimate Partner Violence Reports from Twitter

2021 ◽  
Author(s):  
Mohammed Ali Al-Garadi ◽  
Sangmi Kim ◽  
Yuting Guo ◽  
Elise Warren ◽  
Yuan-Chi Yang ◽  
...  
Keyword(s):  
Social Media ◽  
Intimate Partner Violence ◽  
Content Analysis ◽  
Partner Violence ◽  
Large Scale ◽  
Class Imbalance ◽  
Intimate Partner ◽  
Public Health Issue ◽  
Automatic Identification ◽  
Model Errors

Background Intimate partner violence (IPV) is a preventable public health issue that affects millions of people worldwide. Approximately one in four women are estimated to be or have been victims of severe violence at some point in their lives, irrespective of their age, ethnicity, and economic status. Victims often report IPV experiences on social media, and automatic detection of such reports via machine learning may enable the proactive and targeted distribution of support and/or interventions for those in need. Methods We collected posts from Twitter using a list of keywords related to IPV. We manually reviewed subsets of retrieved posts, and prepared annotation guidelines to categorize tweets into IPV-report or non-IPV-report. We manually annotated a random subset of the collected tweets according to the guidelines, and used them to train and evaluate multiple supervised classification models. For the best classification strategy, we examined the model errors, bias, and trustworthiness through manual and automated content analysis. Results We annotated a total of 6,348 tweets, with inter-annotator agreement (IAA) of 0.86 (Cohen's kappa) among 1,834 double-annotated tweets. The dataset had substantial class imbalance, with only 668 (~11%) tweets representing IPV-reports. The RoBERTa model achieved the best classification performance (accuracy: 95%; IPV-report F1-score 0.76; non-IPV-report F1-score 0.97). Content analysis of the tweets revealed that the RoBERTa model sometimes misclassified as it focused on IPV-irrelevant words or symbols during decision making. Classification outcome and word importance analyses showed that our developed model is not biased toward gender or ethnicity while making classification decisions. Conclusion Our study developed an effective NLP model to identify IPV-reporting tweets automatically and in real time. The developed model can be an essential component for providing proactive social media based intervention and support for victims. It may also be used for population-level surveillance and conducting large-scale cohort studies.

scholarly journals Vindication, virtue, and vitriol

2020 ◽  
Vol 3 (2) ◽  
pp. 401-443 ◽  
Author(s):  
Tracie Farrell ◽  
Genevieve Gorrell ◽  
Kalina Bontcheva
Keyword(s):  
Social Media ◽  
Mixed Methods ◽  
Large Scale ◽  
Hate Speech ◽  
Mixed Methods Study ◽  
Citizen Engagement ◽  
Public Officials ◽  
Online Abuse

AbstractCOVID-19 has given rise to a lot of malicious content online, including hate speech, online abuse, and misinformation. British MPs have also received abuse and hate on social media during this time. To understand and contextualise the level of abuse MPs receive, we consider how ministers use social media to communicate about the pandemic, and the citizen engagement that this generates. The focus of the paper is on a large-scale, mixed-methods study of abusive and antagonistic responses to UK politicians on Twitter, during the pandemic from early February to late May 2020. We find that pressing subjects such as financial concerns attract high levels of engagement, but not necessarily abusive dialogue. Rather, criticising authorities appears to attract higher levels of abuse during this period of the pandemic. In addition, communicating about subjects like racism and inequality may result in accusations of virtue signalling or pandering by some users. This work contributes to the wider understanding of abusive language online, in particular that which is directed at public officials.

scholarly journals Archival Data Thinking and Practices for Social Media Collections

2021 ◽  
Author(s):  
Lizhou Fan
Keyword(s):  
Social Media ◽  
Large Scale ◽  
Data Science ◽  
Hate Speech ◽  
Research Direction ◽  
Data Driven ◽  
Future Research ◽  
Archival Data ◽  
Data Collections ◽  
Rapid Processing

In the Web 2.0 Era, most social media archives are born digital and large-scale. With an increasing need for processing them at a fast speed, researchers and archivists have started applying data science methods in managing social media data collections. However, many of the current computational or data-driven archival processing methods are missing the critical background understandings like “why we need to use computational methods,” and “how to evaluate and improve data-driven applications.” As a result, many computational archival science (CAS) attempts, with comparatively narrow scopes and low efficiencies, are not sufficiently holistic. In this talk, we first introduce the proposed concept of “Archival Data Thinking” that highlights the desirable comprehensiveness in mapping data science mindsets to archival practices. Next, we examine several examples of implementing “Archival Data Thinking” in processing two social media collections: (i) the COVID-19 Hate Speech Twitter Archive (CHSTA) and (ii) the Counter-anti-Asian Hate Twitter Archive (CAAHTA), both of which are with millions of records and their metadata, and needs for rapid processing. Finally, as a future research direction, we briefly discuss the standards and infrastructures that can better support the implementation of “Archival Data Thinking”.

scholarly journals Ethical and technical challenges of AI in tackling hate speech

2021 ◽  
Vol 29 ◽  
Author(s):  
Diogo Cortiz ◽  
Arkaitz Zubiaga
Keyword(s):  
Social Media ◽  
Large Scale ◽  
Information Overload ◽  
Scientific Literature ◽  
Hate Speech ◽  
Freedom Of Expression ◽  
Speech Detection ◽  
Detection Algorithms ◽  
Technical Challenges

In this paper, we discuss some of the ethical and technical challenges of using Artificial Intelligence for online content moderation. As a case study, we used an AI model developed to detect hate speech on social networks, a concept for which varying definitions are given in the scientific literature and consensus is lacking. We argue that while AI can play a central role in dealing with information overload on social media, it could cause risks of violating freedom of expression (if the project is not well conducted). We present some ethical and technical challenges involved in the entire pipeline of an AI project - from data collection to model evaluation - that hinder the large-scale use of hate speech detection algorithms. Finally, we argue that AI can assist with the detection of hate speech in social media, provided that the final judgment about the content has to be made through a process with human involvement.

Change of Attitude, Technology and Practice: Identifying the Change for Increased Value Creation with Customer Co-creation

2017 ◽  
Vol 5 (1) ◽  
pp. 70-82
Author(s):  
Soumi Paul ◽  
Paola Peretti ◽  
Saroj Kumar Datta
Keyword(s):  
Social Media ◽  
New Product Development ◽  
Value Creation ◽  
Large Scale ◽  
Customer Orientation ◽  
Customer Relationships ◽  
Future Research ◽  
Management Competencies ◽  
Business Decisions ◽  
Prime Concern

Building customer relationships and customer equity is the prime concern in today’s business decisions. The emergence of internet, especially social media like Facebook and Twitter, changed traditional marketing thought to a great extent. The importance of customer orientation is reflected in the axiom, “The customer is the king”. A good number of organizations are engaging customers in their new product development activities via social media platforms. Co-creation, a new perspective in which customers are active co-creators of the products they buy and use, is currently challenging the traditional paradigm. The concept of co-creation involving the customer’s knowledge, creativity and judgment to generate value is considered not only an upcoming trend that introduces new products or services but also fitting their need and increasing value for money. Knowledge and innovation are inseparable. Knowledge management competencies and capacities are essential to any organization that aspires to be distinguished and innovative. The present work is an attempt to identify the change in value creation procedure along with one area of business, where co-creation can return significant dividends. It is on extending the brand or brand category through brand extension or line extension. This article, through an in depth literature review analysis, identifies the changes in every perspective of this paradigm shift and it presents a conceptual model of company-customer-brand-based co-creation activity via social media. The main objective is offering an agenda for future research of this emerging trend and ensuring the way to move from theory to practice. The paper acts as a proposal; it allows the organization to go for this change in a large scale and obtain early feedback on the idea presented. 

Pembelajaran Integrasi tentang Etika Penggunaan Media Sosial dalam Materi Ajar Pendidikan Agama Islam di Sekolah Menangah Atas

2019 ◽  
Vol 3 (1) ◽  
pp. 72
Author(s):  
Irfan Afandi
Keyword(s):  
Social Media ◽  
Industrial Revolution ◽  
Hate Speech ◽  
Islamic Education ◽  
Learning Models ◽  
Negative Effects ◽  
Education Material ◽  
Use Of Social Media ◽  
The Waves ◽  
Critical Reason

The humanitarian problem in the development of the industrial revolution 4.0 is very complex and is at the stage of worrying. No human being separated from the effect of the waves. High school is active users (user) of the results of the industrial revolution the 4.0. The problem that arises in the use of social media including the demise of expertise, the dissemination of hate speech and fabricated news. Teaching Islamic education material should be able to respond to this by providing normative information in the Qur'an and Hadith so that students can escape from its negative effects. One of the solutions offered was to integrate these materials with integratsi learning models in the themes that have been arranged in the school's learning policy. Integrating this material must through the phases between the awarding phase of learning, information or materials to grow a critical reason, generate hypotheses and generalities.

Identity concerns drive belief: The impact of partisan identity on the belief and dissemination of true and false news

2018 ◽  
Author(s):  
Andrea Pereira ◽  
Jay Joseph Van Bavel ◽  
Elizabeth Ann Harris
Keyword(s):  
Social Media ◽  
Political System ◽  
Political Identity ◽  
Social Goals ◽  
Fake News ◽  
Political Beliefs ◽  
System P ◽  
False News ◽  
Democrats And Republicans ◽  
The Impact

Political misinformation, often called “fake news”, represents a threat to our democracies because it impedes citizens from being appropriately informed. Evidence suggests that fake news spreads more rapidly than real news—especially when it contains political content. The present article tests three competing theoretical accounts that have been proposed to explain the rise and spread of political (fake) news: (1) the ideology hypothesis— people prefer news that bolsters their values and worldviews; (2) the confirmation bias hypothesis—people prefer news that fits their pre-existing stereotypical knowledge; and (3) the political identity hypothesis—people prefer news that allows their political in-group to fulfill certain social goals. We conducted three experiments in which American participants read news that concerned behaviors perpetrated by their political in-group or out-group and measured the extent to which they believed the news (Exp. 1, Exp. 2, Exp. 3), and were willing to share the news on social media (Exp. 2 and 3). Results revealed that Democrats and Republicans were both more likely to believe news about the value-upholding behavior of their in-group or the value-undermining behavior of their out-group, supporting a political identity hypothesis. However, although belief was positively correlated with willingness to share on social media in all conditions, we also found that Republicans were more likely to believe and want to share apolitical fake new. We discuss the implications for theoretical explanations of political beliefs and application of these concepts in in polarized political system.

Choice Matters

2018 ◽  
Author(s):  
Gordon Moore ◽  
John A. Quelch ◽  
Emily Boudreau
Keyword(s):  
Public Policy ◽  
Social Media ◽  
Healthcare Provider ◽  
Healthcare System ◽  
Consumer Choice ◽  
Marketing Management ◽  
Appropriate Use ◽  
System P ◽  
The U.S

Choice Matters: How Healthcare Consumers Make Decisions (and Why Clinicians and Managers Should Care) is a timely and thoughtful exploration of the controversial role of consumers in the U.S. healthcare system. In most markets today, consumers have more options and autonomy than ever before. Empowered consumers easily shop around for products and services that better meet their needs, and they widely share their reviews on social media to inform and influence other consumers. Businesses have responded with better experiences and prices to compete for consumers’ business. Though healthcare has lagged behind other industries in this respect, there is a rising tide of interest in consumer choice and empowerment in healthcare markets. However, most healthcare provider organizations, individual doctors, and health insurers are unprepared to consider patients as consumers. The authors draw upon the fields of medicine, marketing, management, psychology, and public policy as they take a substantive, in-depth look at consumer choice and point out its appropriate use, as well as its limitations. This book addresses perplexing issues, such as how healthcare differs from other consumer-driven markets, how consumers make healthcare decisions, and how increased consumer choice in healthcare can not only aid and empower American consumers but also improve the overall healthcare system.

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