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15 results for “propaganda”
Dataset for "Common Propaganda Devices in Late Republican Coinage, 79-31 BCE"
<p>Dataset for "Common Propaganda Devices in Late Republican Coinage, 79-31 BCE" published in "Numismatica e Antichità Classiche" 50, 2021</p>
Supplementary File: Entertainment interspersed with propaganda: How non-legacy-news accounts deliver explicitly political content to mass audiences on Russia's most popular social network VK
<p>Supplementary file and dataset for the paper "Entertainment interspersed with propaganda: How non-legacy-news accounts deliver explicitly political content to mass audiences on Russia’s most popular social network VK"</p>
Multi-label Tweet Dataset for Textual Propaganda Detection related to anti-CAA protest in India (2019-2021)
<p>This is a collection of English Tweets about the Citizenship (Amendment) Bill protests that occurred in India in 2019-2021. The dataset contains tweet instances multiple labels for identified propaganda techniques. The data set consists of tweet ids, hashtags used, and corresponding propaganda techniques. Labels have been automatically generated using Weak Supervision. </p> <p>As of 2023, there are very limited textual propaganda detection dataset for Tweets. This dataset is released to facilitate future research as propaganda has become omnipresent in modern social media. </p> <p> </p> <p> </p>
Propaganda and fake news on the war in Ukraine: data from Russian-speaking social media communities
<p>The data set contains posts from social media networks popular among Russian-speaking communities. Information was searched based on pre-defined keywords ("war", "special military operation", etc.) and is mainly related to the ongoing war in Ukraine with Russia. After a thorough review and analysis of the data, both propaganda and fake news were identified. The collected data is anonymized. Feature engineering and text preprocessing can be applied to obtain new insights and knowledge from this data set. The data set is useful for the study of information wars and propaganda identification.</p>
Russian court decisions on article 6.21 "Propaganda of non-traditional sexual relationships" (Code of Administrative Offences)
<p>The <strong>zip</strong> archive contains 338 <strong>txt</strong> files of Russian court decisions on article 6.21 "Propaganda of non-traditional sexual relationships" (Code of Administrative Offences). The source is Russian online database of juridical decisions <a href="http://sudact.ru">sudact.ru</a>.</p>
SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles
<p>This dataset contains the files and annotations for <a href="https://propaganda.qcri.org/semeval2020-task11/index.html">SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles</a>. The task was composed by two subtasks: span identification (SI) and technique classification (TC). This dataset includes the following:</p> <ul> <li>The text files for training, development, and testing sets for both the SI and the TC tasks.</li> <li>The gold-standard files for the training sets, for both the SI and the TC task</li> </ul> <p>Our propaganda identification initiative remains active. We keep a <a href="https://propaganda.qcri.org/ptc/leaderboard.php">live leader-board</a> reporting the performance of models submited up to date.</p> <p><strong>Reference</strong></p> <p>Giovanni Da San Martino, Alberto Barrón-Cedeño, Henning Wachsmuth, Rostislav Petrov, and Preslav Nakov. 2020. <a href="https://propaganda.qcri.org/">Task 11: Detection of Propaganda Techniques in News Articles</a>. In Proceedings of the 14th International Workshop on Semantic Evaluation (SemEval 2020). Barcelona, Spain (2020)</p> <p> </p> <pre><code>@InProceedings{SemEval20-11-DaSanMartino, author = "Da San Martino, Giovanni and Barr\'{o}n-Cede\~no, Alberto and Wachsmuth, Henning and Petrov, Rostislav and Nakov, Preslav", title = "{SemEval}-2020 Task 11: {D}etection of Propaganda Techniques in News Articles", pages = "", abstract = "We describe the outcome of the SemEval 2020 Task 11 on the detection of propaganda in news articles. We present two tasks. In the first task, systems are asked to identify specific text spans in a free text where propaganda is being applied. In the second task, systems are asked to identify the propaganda technique being applied in a text span. We describe the construction of the evaluation framework (dataset and evaluation metrics) as well as the approaches explored by the different participants. ", crossref = "SemEval20" }</code></pre> <p> </p>
Supporting data for: Výpočtová propaganda: konceptuálna diskusia a prehľad (eng. Computational propaganda: a conceptual discussion and review)
<p><em>Supporting data for a Literature Review.</em></p> <p><em>Abstract: Computational propaganda is a relatively new term introduced by P.N. Howard and S. C. Woolley. The term is nowadays being mainly discussed in the context of shaping public opinion during various political events in the United States, the United Kingdom, France, as well as in other countries. This article represents a literature review of computational propaganda using a quantitative research design. In the article we also present the first Slovak definition of computational propaganda as using Information and communication technologies for mass production and mass distribution of misleading information. </em></p>
Montages for "The flood, the traitors, and the protectors: affect and white identity in the Internet Research Agency's Islamophobic propaganda on Twitter"
<p>These are the four montages associated with the publication, "The flood, the traitors, and the protectors: affect and white identity in the Internet Research Agency’s Islamophobic propaganda on Twitter", published in <em>Ethnic & Racial Studies. </em>This repository provides access to the full-resolution images as discussed in the article.</p> <p>The images in this dataset come from data provided by Twitter's Moderation Research Consortium.</p> <p>The article is accepted and in press, and will be published in 2024. Please contact the corresponding author, b.ganesh@uva.nl, to read the paper.</p>
Institutions and Cultural Diversity: Effects of Democratic and Propaganda Processes on Local Convergence and Global Diversity.
<p>In a connected world where people influence each other, what can cause a globalized monoculture, and which measures help to preserve the coexistence of cultures? Previous research has shown that factors such as homophily, population size, geography, mass media, and type of social influence play important roles. In the present paper, we investigate for the first time the impact that institutions have on cultural diversity. In our first three studies, we extend existing agent-based models and explore the effects of institutional influence and agent loyalty. We find that higher institutional influence increases cultural diversity, while individuals' loyalty to their institutions has a small, preserving effect. In three further studies, we test how bottom-up and top-down processes of institutional influence impact our model. We find that bottom-up democratic practices, such as referenda, tend to produce convergence towards homogeneity, while top-down information dissemination practices, such as propaganda, further increase diversity. In our last model – an integration of bottom-up and top-down processes into a feedback loop of information – we found that when democratic processes are rare, the effects of propaganda are amplified, i.e. more diversity emerges; however, when democratic processes are common, they are able to neutralize or even reverse this propaganda effect. Importantly, our models allow for control over the full spectrum of diversity, so that a manipulation of our variables can result in preferred levels of diversity, which will be useful for the study of other factors in the future. We discuss possible mechanisms behind our results, possible applications, and implications for political and social sciences.</p>
H-Prop and H-Prop-News Propaganda Datasets in Hindi
<p>The H-Prop dataset contains 28,630 articles created by translating a portion of Proppy Corpus in Hindi. Each article is labeled as either “propagandistic” (positive class) or “non-propagandistic” (negative class). The labeling done indirectly in Proppy corpus using a technique known as distant supervision is retained. </p> <p>The H-Prop-News dataset contains 5,500 Hindi News articles collected from 30+ prominent Hindi News websites. Each article is labeled as either “propagandistic” (positive class) or “non-propagandistic” (negative class). The labeling was done by human annotators and the inter-annotator agreement using Cohen’s Kappa measure observed is 0.81.</p> <p>## Data format</p> <p>We provide the H-Prop dataset in three tsv files, including training, testing and validation partitions. The H-Prop-News dataset is provided in csv files including training, testing and validation partitions.</p> <p>Each line represents one article in H-Prop dataset with the following information:</p> <p>1. article_text: the text of the article translated from Proppy corpus.<br> 2. propaganda_label: label for articles retained from Proppy corpus.</p> <p>Each line represents one article in H-Prop-News dataset with the following information:</p> <p>1. news_website: Name of the news source website<br> 2. article_url: the direct URL for the published article in its source website<br> 3. news_headline: news headline<br> 4. article_text: the text of the article retrieved via parsehub tool<br> 5. propaganda_label: label for articles</p> <p>## About</p> <p>The H-Prop dataset was translated using IBM Watson Language Translator. </p> <p>## Credit</p> <p>Please cite the dataset as:<br> [HProp-News] Deptii Chaudhari, Ambika Pawar, and Alberto Barrón-Cedeño. 2022. H-Prop and H-Prop-News: Computational Propaganda Datasets in Hindi. doi: 10.5281/zenodo.5828240</p> <p>## Authors</p> <p>Deptii Chaudhari;<br> Ambika Pawar;<br> Alberto Barrón-Cedeno</p>
Reflections on Music and Propaganda
<p>In <em>Reflections on Music and Propaganda</em>, the electroacoustic music composer Luis Velasco-Pufleau and the visual artist Sergio Santamaría Borges explore the emotional dimension of humanitarian songs and the political implications of media narratives which accompanied them. The video installation deconstructs recurrent and redundant humanitarian narratives through the montage, collage, and overlapping of statements from “humanitarian” musicians, TV images that accompanied the songs, and excerpts of video clips, all of them produced between 1984 and 2014. No other material was used or added, just images, words, gestures, and sounds that were scattered in a flow of information, from the famine caused by the 1983–1985 Ethiopian civil war to the Ebola virus outbreak in 2014.</p> <p><em>Reflections on Music and Propaganda</em> was commissioned by Städtische Galerie im Lenbachhaus und Kunstbau München for the exhibition “After the Fact. Propaganda in the 21st century”.<br>Curator: Stephanie Weber<br>Städtische Galerie im Lenbachhaus und Kunstbau München<br>30 May – 17 September 2017</p>
Analysing state-backed propaganda websites: a new dataset and linguistic study (public dataset)
<p>This is the dataset accompanying the EMNLP 2023 paper "Analysing state-backed propaganda websites: a new dataset and linguistic study".</p> <p>For copyright and liability reasons, we do not publicly distribute the complete dataset. Instead, we provide the software used to create the dataset (DOI: <a href="https://doi.org/10.5281/zenodo.10008086">10.5281/zenodo.10008086</a>) and a list containing the URLs of all the posts in the full dataset (this repository).</p> <p><strong>To reconstruct our dataset</strong>: use the software to extract the sites, then filter the posts to the corresponding URL list. Please note that some posts may no longer be available or may have been modified.</p> <p><strong>If you are researching disinformation, propaganda, or a relevant field:</strong> please contact the authors, we may be able to provide you with the original dataset.</p>
Dataset to Analyze Propaganda in Tweets From Politically Biased Sources
<p><span>Our dataset consists of 32,047 tweets from 44 ac</span><span>count associated with 11 news outlets downloaded between</span><br><span>27th</span><span> </span><span>September 2022 to 3rd</span><span> </span><span>October 2022, from Twitter using </span><span>Twitter Streaming API.</span><br><span>Each tweet is a record that contains the tweet id, number </span><span>of likes, retweet count, isretweeted status, associated bias of</span><br><span>the new outlets according to AllSides Media Bias rating</span><span>, </span><span>and model prediction(1 for propaganda and 0 for non-propaganda)</span></p>
Analysing state-backed propaganda websites: a new dataset and linguistic study (complete dataset)
<p>This is the complete dataset accompanying the EMNLP 2023 paper "Analysing state-backed propaganda websites: a new dataset and linguistic study".</p><p>Please contact the authors for access.</p><p>Alternatively, you can reproduce this dataset using the accompanying software (DOI: <a href="https://doi.org/10.5281/zenodo.10008086">10.5281/zenodo.10008086</a>) and a list of post URLs included in the complete dataset (DOI: <a href="https://doi.org/10.5281/zenodo.10007383">10.5281/zenodo.10007383</a>)</p>
propaganda detection
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