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Dataset results
17 results for “Ideology”
EMOFORTE- Ideological Map of Emotions in Turkey
<p>EMOFORTE Project Deliverable: An ideological map of emotions with a comparative-synchronic approach to the discourses of Turkish political parties on Foreign Policy at the nexus of national identity and Europe as its significant Other. </p> <p> </p> <p>This diagram has been prepared as a part of EMOFORTE Project that has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No.896311</p>
Young people's media use and adherence to preventive measures in the "infodemic": Is it masked by political ideology?
<p>Data to replicate the publication "Young people's media use and adherence to preventive measures in the “infodemic”: Is it masked by political ideology?". This publication examines the role of political ideology and political extremism for COVID-19 information seeking and preventive behaviour with data of the COVIDisc project. COVIDisc investigates how young people aged 15 to 34 years perceive the discussion in the Coronavirus Pandemic, which messages reach them, what media they use to inform themselves and how they experience the situation. en</p>
Multi-ideology ISIS/Jihadist White Supremacist (MIWS) Dataset for Multi-class Extremism Text Classification
<p>**************Information on how to use our Multi-ideology ISIS/Jihadist White Supremacist Dataset(MIWS)for Multi-class Extremism Text Classification ************</p> <p>Folder name: Seed_MIWS<br> Sub Folder 1 : Seed_Dataset<br> Inside this folder there are two .csv files.<br> 1) ISIS/Jihadist_Seed_Dataset<br> 2) White_Supremacist_Seed_Dataset</p> <p>These files have common features as:<br> ***************************** Common Features in Seed ******************************************************<br> *********Source :- Contains Author, Article Name or Hyperlink to Article************************************<br> *********Type_of_Source :- Whether Source is Research Article or Report or Website**************************<br> *********Text :- Contains Extremist Text provided in Source*************************************************<br> *********Ideology :- Ideology of Text mentioned in Source i.e. ISIS/Jihadist or White Supremacist***********<br> *********Label :- Labels for Text provided by Source i.e. Propaganda, Radicalization or Recruitment*********<br> *********Geographical_Location :- Location mentioned in Text. Geographical Location is manually identified**<br> *********Author_Country_Affiliation :- Country of origin of Research Article, Report or Website in Source***</p> <p>Sub Folder 2 : MIWS<br> Inside this folder ther is one .csv file:</p> <p>It contains features as:<br> *****************************Features in MIWS********************************************************************************<br> **********Tweet_ID :- Unique Identification for a Tweet provided by Twitter**************************************************<br> **********Created_Date :- Date and Time at whic Tweet was created or posted**************************************************<br> **********Geo_Enabled :- Boolean value. True if location is made public by User**********************************************<br> **********Geographical_Location :- Manually extracted list of Locations within the tweet. 'Undefined' if no location present*<br> **********Ideology :- Manually provided during Tweet Collection i.e. ISIS/Jihadist or White Supremacist**********************<br> **********Labels :- Annotated by comparing with Seed, i.e. Propaganda, Radicalization and Recruitment***********************</p> <p>MIWS file can be used to collect tweets and train model for extremism detection.</p>
Transcripció de tres entrevistes sobre ideologies lingüístiques i teoria implícita de traducció
<p>Aquest estudi explora la relació hipotètica entre les ideologies lingüístiques de tres estudiantes del grau en Traducció i Interpretació de la Universitat Jaume I i la teoria implícita de traducció que aquestes estudiantes mostren. Per a dur a terme l'anàlisi, s’han portat a cap tres entrevistes semiestructurades que tracten els conceptes de teoria implícita de traducció i ideologies lingüístiques de la llengua catalana, el paper de l'educació i l'entorn i la seua percepció de la minorització del català i de les desigualtats (i jerarquies) socials i polítiques. En aquest document podeu veure les transcripcions de les entrevistes esmentades.</p>
Spatiotemporal impacts of ideology and social vulnerability on COVID-19 for the United States
<p><span>In early 2020, the Coronavirus Disease 19 (COVID-19) rapidly spread across the United States, exhibiting significant geographic </span><span>variability. While several studies have examined the predictive relationships of differing factors on COVID-19 deaths, few have </span><span>looked at spatiotemporal variation at refined geographic scales. The objective of this analysis is to examine county-level </span><span>spatiotemporal variation of COVID-19 deaths in association with socioeconomic, health, demographic, and political factors, </span><span>using regionalized multivariate regression as well as nationwide geographically weighted random forest (GWRF) models. </span><span>Regionalized regression results across three time windows—pandemic onset until May 2021, May 2021 through November </span><span>2021, and December 2021 until April 2022—suggest that existing measures of social vulnerability for disaster preparedness </span><span>(SVI) are associated with a higher degree of mortality from COVID-19. In comparison, GWRF models provide a more robust </span><span>evaluation of feature importance and prediction, exposing the importance of local features, such as obesity, which is obscured </span><span>by regional delineation. Overall, GWRF results indicate this more nuanced modeling strategy is useful for capturing the diverse </span><span>spatial and temporal nature of the COVID-19 pandemic.</span></p>
Parties' Ideological Positions on the Digital Transition to Platform Societies: Dataset
<p>The dataset showcases an original classification of the ideological positions on the digital transition to platform societies by 29 parties in 4 Western European countries. The codebook details the definition of the coding units. The coding files illustrates how the paragraphs are sorted into the indicators' scores. </p>
The cognitive and perceptual correlates of ideological attitudes: a data-driven approach
<p>Data and analysis scripts for: </p> <p>Zmigrod L, Eisenberg IW, Bissett PG, Robbins TW, Poldrack RA. 2021 The cognitive and perceptual correlates of ideological attitudes: a data-driven approach. Phil. Trans. R. Soc. B 20200424. https://doi.org/10.1098/rstb.2020.0424</p>
Dataset for the paper "Ideology and identity in grammar: A diachronic-quantitative approach to language standardisation processes in Ancient Greek"
<p>This is the dataset for the paper "Ideology and identity in grammar: A diachronic-quantitative approach to language standardisation processes in Ancient Greek"</p>
Data, code snippets, and resources of BMF CP51: Political ideology, climate change belief, and potable water reuse willingness in the USA
<p>The dataset, data description, code snippets, and figures related to the Bayesian analysis of BMF CP 51 on SM3D Portal were uploaded to Zenodo to enhance transparency and assist in later replication and validation (https://mindsponge.info/posts/246). The original dataset can be found at: https://www.sciencedirect.com/science/article/pii/S2352340920301839</p>
Correlates of Political Correctness and Woke Ideology (data and codebook)
<p>This study explored the different correlates of political correctness and Woke philosophy. Based on the existing<br> literature, a new 42-item questionnaire called Controversial Beliefs was created and completed by 400 adults.<br> Participants were invited to write comments on each item and had the option to not respond (Prefer not to say). Various factors were devised based on a content analysis conducted around the themes of Race, Gender and Feminism, which had acceptable<br> internal reliability. </p>
A Computational Analysis of the Ideological Landscape of Turkey and Electoral Behavior
Open the record for dataset details and reuse information.
Training data for the shared task Ideology and Power Identification in Parliamentary Debates (2024)
<p>This dataset contains a selection of speeches from <a href="https://www.clarin.eu/parlamint">ParlaMint</a> corpora (version 4.0) as the training set for the shared task on "<a href="https://touche.webis.de/clef24/touche24-web/ideology-and-power-identification-in-parliamentary-debates.html">Ideology and Power Identification in Parliamentary Debates</a>" in <a href="https://clef2024.imag.fr/">CLEF 2024</a>.</p> <p>All files are tab-separated text files with the following fields:</p> <ul> <li>"<em>id</em>" is a unique (arbitrary) ID for each text.</li> <li>"<em>speaker</em>" is a unique (arbitrary) ID for each speaker. There may be multiple speeches from the same speaker.</li> <li>"<em>sex</em>" is the (binary/biological) sex of the speaker. This information is collected from varying sources (typically data published by the respective parliament), and in some cases it may be unspecified or unknown.</li> <li>"<em>text</em>" is the transcribed text of the parliamentary speech. Real examples may include line breaks, and other special sequences escaped or quoted.</li> <li>"<em>text_en</em>" is an automatic English translation of the corresponding text. This field may be empty (obviously) for speeches in English, but the translations may be missing for a small number of non-English speeches as well.</li> <li>"<em>label</em>" is the binary/numeric label. For political orientation, 0 is left and 1 is right. For power identification 0 indicates coalition (or governing party) and 1 indicates opposition.</li> </ul> <p>File names indicate the task and the parliament. We provide data from the following national and regional parliaments.</p> <ul> <li>Austria (at)</li> <li>Bosnia and Herzegovina (ba)</li> <li>Belgium (be)</li> <li>Bulgaria (bg)</li> <li>Czechia (cz)</li> <li>Denmark (dk)</li> <li>Estonia (ee) [only political orientation]</li> <li>Spain (es)</li> <li>Catalonia (es-ct)</li> <li>Galicia (es-ga)</li> <li>Basque Country (es-pv) [only power]</li> <li>Finland (fi)</li> <li>France (fr)</li> <li>Great Britain (gb)</li> <li>Greece (gr)</li> <li>Croatia (hr)</li> <li>Hungary (hu)</li> <li>Iceland (is) [only political orientation]</li> <li>Italy (it)</li> <li>Latvia (lv)</li> <li>The Netherlands (nl)</li> <li>Norway (no) [only political orientation]</li> <li>Poland (pl)</li> <li>Portugal (pt)</li> <li>Serbia (rs)</li> <li>Sweden (se) [only political orientation]</li> <li>Slovenia (si)</li> <li>Turkey (tr)</li> <li>Ukraine (ua)</li> </ul> <p>The number of training instances and the class imbalance differs for each training set. We do not provide a fixed validation split. Please see the <a href="https://touche.webis.de/clef24/touche24-web/ideology-and-power-identification-in-parliamentary-debates.html">shared task website</a> for further description of the data set and the sampling process.</p>
Replication package for: Moral Universalism and the Structure of Ideology
<p>This package contains replication material (survey procedures, code, data) for the exhibits in Enke, Rodriguez-Padilla, and Zimmermann (forthcoming), "Moral Universalism and the Structure of Ideology." Review of Economic Studies.</p>
Test data for the shared task Ideology and Power Identification in Parliamentary Debates 2024
<p>This dataset contains a selection of speeches from <a href="https://www.clarin.eu/parlamint">ParlaMint</a> corpora (version 4.0) as the test set for the shared task on "<a href="https://touche.webis.de/clef24/touche24-web/ideology-and-power-identification-in-parliamentary-debates.html">Ideology and Power Identification in Parliamentary Debates</a>" in <a href="https://clef2024.imag.fr/">CLEF 2024</a>. The format of the files are similar to the <a title="training set" href="10450640">training set</a>, with the exception that the labels are not provided in this data set.</p>
Purity, Politics, and Polarization: Political Ideology Moderates Shifts in Moral Purity Beliefs to Economic Threat
<p>Study 1 Variables:</p> <p>Threat: Var00001 (1=threat, 2=control)</p> <p>Anxiety manipulation check: Anxiety</p> <p>Moral Foundations Endorsement: MFQ_HARM_AVG, MFQ_FAIRNESS_AVG, MFQ_INGROUP_AVG, MFQ_AUTHORITY_AVG, MFQ_PURITY_AVG</p> <p>Political Ideology (higher scores mean the participant is more conservative): PolitID</p> <p>Pro-life New Zealand charity: Purity_donation_true</p> <p> </p> <p>Study 2 Variables: </p> <p>Threat: Condition (1=threat, 0=control)</p> <p>Anxiety manipulation check: Anxiety</p> <p>Purity Endorsement: MFQ_HARM_AVG, MFQ_FAIRNESS_AVG, MFQ_INGROUP_AVG, MFQ_AUTHORITY_AVG, MFQ_PURITY_AVG</p> <p>Political Ideology (higher scores mean the participant is more conservative): POLiD</p> <p>Casual sex disapproval: xCASUAL_SEX</p>
Training data for the shared task Ideology and Power Identification in Parliamentary Debates - with errors please do not use!
<p><strong>This dataset is an early release with errors. Please do not use this data set. The official dataset for the shared task will be announced on <a href="https://touche.webis.de/clef24/touche24-web/ideology-and-power-identification-in-parliamentary-debates.html">the shared task webpage</a>.</strong></p>
Data for Reported user-generated online hate speech: The 'ecosystem', frames, and ideologies
<p>This is the dataset for the article entitled Reported user-generated online hate speech: The 'ecosystem', frames, and ideologies. The same dataset is provided in two different formats: comma-separated values (.csv) and Excel format (.xlsx). A basic legend to the data is provided separately in the corresponding PDF document. An extended legend to the data is available at: <strong><a href="https://doi.org/10.5281/zenodo.6656185">https://doi.org/10.5281/zenodo.6656185</a></strong>.</p>
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