Dataset of Propaganda and Non-Propaganda Poster Titles

Published: 29 November 2024| Version 2 | DOI: 10.17632/mkvcvnzsnp.2
Contributors:
Riaz Mahmood, Intiajul Alam Shah, Md. Golam Rabiul Alam

Description

The dataset consists of titles from propaganda and non-propaganda posters, categorized for binary classification research. These titles capture textual elements from materials designed to influence or convey messages, focusing on distinguishing propaganda from non-propaganda content. Labeled with binary tags (propaganda/non-propaganda), the dataset supports studies on text classification, exploring linguistic and stylistic differences. Sourced and labeled for clarity and real-world relevance, it enables comparative analysis of linguistic trends, stylistic features, and propaganda's role in media. This is raw text data, requiring preprocessing steps such as data cleaning, removing special characters, and other standard text preparation techniques. Two folders containing sample poster images are also included: one for propaganda posters and the other for non-propaganda posters. This resource is valuable for researchers in computer science, social sciences, and media studies investigating automated detection, language analysis, and public perception of propaganda.

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Categories

History, Political Science, Natural Language Processing, Machine Learning

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