Radical Text Detection based on Stylometry

In this modern era, many people use social media easily and freely. One of the social media used is Twitter. The reason people use Twitter is that they can express their opinion freely. However, this freedom does not always have a positive impact on other Twitter users. One of the negative impacts for users is that they can spread radical content. Therefore, this research aims to detect whether a tweet contains radical elements or not using the backpropagation neural network method. The process is carried out by taking data on Twitter, after which the preprocessing process is carried out. Then the data is processed using imbalanced handling, where the data is divided into oversampling and undersampling data. After the data is divided, the next process is to do stopword and then look for accuracy by comparing different epoch values, namely 100, 150, 200, and 250. The best epoch value obtained is 200, with a final accuracy result of 86%.

show abstract

“…In research [7], the author used machine learning to classify radical text. The result obtained in this study reached 92,3% using random forest.…”

Section: Introductionmentioning

confidence: 99%

Radicalism Speech Detection in Indonesia on Twitter Using Backpropagation Neural Network Method

Musa

Sibaroni

2022

JoSYC

View full text Add to dashboard Cite

show abstract

A survey on extremism analysis using natural language processing: definitions, literature review, trends and challenges

Torregrosa

Bello-Orgaz

Martínez‐Cámara

et al. 2022

J Ambient Intell Human Comput

View full text Add to dashboard Cite

Extremism has grown as a global problem for society in recent years, especially after the apparition of movements such as jihadism. This and other extremist groups have taken advantage of different approaches, such as the use of Social Media, to spread their ideology, promote their acts and recruit followers. The extremist discourse, therefore, is reflected on the language used by these groups. Natural language processing (NLP) provides a way of detecting this type of content, and several authors make use of it to describe and discriminate the discourse held by these groups, with the final objective of detecting and preventing its spread. Following this approach, this survey aims to review the contributions of NLP to the field of extremism research, providing the reader with a comprehensive picture of the state of the art of this research area. The content includes a first conceptualization of the term extremism, the elements that compose an extremist discourse and the differences with other terms. After that, a review description and comparison of the frequently used NLP techniques is presented, including how they were applied, the insights they provided, the most frequently used NLP software tools, descriptive and classification applications, and the availability of datasets and data sources for research. Finally, research questions are approached and answered with highlights from the review, while future trends, challenges and directions derived from these highlights are suggested towards stimulating further research in this exciting research area.

show abstract

Radicalism prevention through education strategies aligned with SDGs in Indonesia: Bibliometric analysis

Handoyo,

Kenayathulla,

Puspita

2024

E3S Web Conf.

View full text Add to dashboard Cite

Religious and national organizations triggered radicalism in Indonesia, which was triggered by ideological, political, and military factors. The research was conducted to investigate the roots of radicalism and methods to overcome it, especially through applying educational approaches aligned with the Sustainable Development Goals (SDGs). Analysis of bibliometric data from the Scopus database from 2013 to 2023 was used to identify research trends and key themes. The study’s findings integrate education, community engagement, media literacy, and political reform to foster a tolerant and inclusive society. Important topics include methods of youth engagement in educational strategies, faith-based and communitybased, the power of religious movements, media effects, and political dynamics. The study results show that educational strategies that support the SDGs can help prevent radicalism by promoting peace, equality, and sustainability. By implementing this strategy, the young generation with global awareness and responsibility is expected to emerge, contributing to creating a peaceful and inclusive society in Indonesia.

show abstract

Radical Text Detection based on Stylometry

Cited by 4 publications

References 0 publications

Radicalism Speech Detection in Indonesia on Twitter Using Backpropagation Neural Network Method

Radicalism Speech Detection in Indonesia on Twitter Using Backpropagation Neural Network Method

A survey on extremism analysis using natural language processing: definitions, literature review, trends and challenges

Radicalism prevention through education strategies aligned with SDGs in Indonesia: Bibliometric analysis

Contact Info

Product

Resources

About