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- Creator:
- Yan, Haoyang MI and Yates, J Frank
- Description:
- The research aims to demonstrate judgment accuracy about other individuals' socio-political opinions produced by prototype matching and base/shift heuristics or people's own strategies (control).
- Keyword:
- judgment accuracy and socio-political opinions
- Citation to related publication:
- Discipline:
- Social Sciences
- Title:
- Judgment Accuracy Experiment Data
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- Creator:
- Budak, Ceren, Goel, Sharad, and Rao, Justin M
- Description:
- Our primary analysis is based on articles published in 2013 by the top thirteen US news outlets and two popular political blogs. To compile the set of articles published by these outlets, we first examined the complete web-browsing records for US-located users who installed the Bing Toolbar, an optional add-on application for the Internet Explorer web browser. For each of the fifteen news sites, we recorded all unique URLs that were visited by at least ten toolbar users, and we then crawled the news sites to obtain the full article title and text. This process resulted in a corpus of 803,146 articles published on the fifteen news sites over the course of a year, with each article annotated with its relative popularity. , Next, we built two binary classifiers using large-scale logistic regression. The first classifier—which we refer to as the news classifier —identifies “news” articles (i.e., articles that would typically appear in the front section of a traditional newspaper). The second classifier—the politics classifier —identifies political news from the subset of articles identified as news by the first classifier. 340,191 (42 percent) were classified as news. On the set of 340,191 news articles, 114,814 (34 percent) were classified as political. , Having identified approximately 115,000 political news articles, we next seek to categorize the articles by topic (e.g., gay rights, healthcare, etc.), and to quantify the political slant of the article. To do so, we turn to human judges recruited via Mechanical Turk to analyze the articles. For every day in 2013, we randomly selected two political articles, when available, from each of the 15 outlets we study, with sampling weights equal to the number of times the article was visited by our panel of toolbar users., Amazon Mechanical Turk Labeling task: To detect and control for possible preconceptions of an outlet’s ideological slant, workers, upon first entering the experiment, were randomly assigned to either a blinded or unblinded condition. In the blinded condition, workers were presented with only the article’s title and text, whereas in the unblinded condition, they were additionally shown the name of the outlet in which the article was published. Each article was then analyzed by two workers, one each from the sets of workers in the two conditions. For each article, each worker completed the following three tasks. First, they provided primary and secondary article classifications from a list of fifteen topics: (1) civil rights; (2) Democrat scandals; (3) drugs; (4) economy; (5) education; (6) elections; (7) environment; (8) gay rights; (9) gun-related crimes; (10) gun rights/regulation; (11) healthcare; (12) international news; (13) national security; (14) Republican scandals; and (15) other. , and Second, workers determined whether the article was descriptive news or opinion. Third, to measure ideological slant, workers were asked, “Is the article generally positive, neutral, or negative toward members of the Democratic Party?” and separately, “Is the article generally positive, neutral, or negative toward members of the Republican Party?” Choices for these last two questions were provided on a five-point scale: very positive, somewhat positive, neutral, somewhat negative, and very negative. To mitigate question-ordering effects, workers were initially randomly assigned to being asked either the Democratic or Republican party question first; the question order remained the same for any subsequent articles the worker rated. Finally, we assigned each article a partisanship score between –1 and 1, where a negative rating indicates that the article is net left-leaning and a positive rating indicates that it is net right-leaning. Specifically, for an article’s depiction of the Democratic Party, the five-point scale from very positive to very negative is encoded as –1, –0.5, 0, 0.5, 1. Analogously, for an article’s depiction of the Republican Party, the scale is encoded as 1, 0.5, 0, –.0.5, –1. The score for each article is defined as the average over these two ratings. Thus, an average score of –1, for example, indicates that the article is very positive toward Democrats and very negative toward Republicans. The result of this procedure is a large, representative sample of political news articles, with direct human judgments on partisanship and article topic.
- Keyword:
- news media, media bias, crowdsourcing, and machine learning
- Citation to related publication:
- https://academic.oup.com/poq/article-abstract/80/S1/250/2223443/?redirectedFrom=fulltext Ceren Budak, Sharad Goel, Justin M. Rao, Fair and Balanced? Quantifying Media Bias through Crowdsourced Content Analysis, Public Opinion Quarterly, Volume 80, Issue S1, 2016, Pages 250–271, https://doi.org/10.1093/poq/nfw007
- Discipline:
- Social Sciences
- Title:
- Quantifying News Media Bias through Crowdsourcing and Machine Learning Dataset
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- Creator:
- Ottaviani, Jim
- Description:
- This random sample of OA articles comes from Deep Blue <deepblue.lib.umich.edu/documents>, the University of Michigan’s institutional repository service. Each OA article has the following characteristics: Prior to a known date (ranging from 2006 to the 2013) these articles—the final published version—were only available by subscription. After that date, they became freely available via Deep Blue. Meanwhile, other articles from the same journal issue as the now-OA article continued to only be available to subscribers. None of the OA articles were self-selected; authors did not choose to deposit the articles in question in Deep Blue, since we made them open via blanket licensing agreements between the publishers and the library.
- Keyword:
- Open access publishing, Scientific publishing, Citation analysis, and Institutional repositories
- Citation to related publication:
- Ottaviani J (2016) The Post-Embargo Open Access Citation Advantage: It Exists (Probably), It’s Modest (Usually), and the Rich Get Richer (of Course). PLoS ONE 11(8): e0159614. https://doi.org/10.1371/journal.pone.0159614
- Discipline:
- Social Sciences
- Title:
- Citations to Open and Closed Access Articles: Treatment and Control Group Data
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- Creator:
- Data-Driven Detroit, Goodspeed, Robert, Reference U.S.A., Veinot, Tiffany C., Yan, Xiang, State of Michigan Department of Elections, and Okullo, Dolorence
- Description:
- The Social Environment refers to characteristics of the people and institutions in a census tract, including: 1) Religious organizations (churches and places of worship); and 2) Voter turnout for the 2012 Presidential Election. Coverage for all data: 10-county Detroit-Warren-Ann Arbor Combined Statistical Area.
- Keyword:
- Voter Turnout, Religious Institutions, Spatial Measures, and Census Tract Level
- Citation to related publication:
- Discipline:
- Health Sciences and Social Sciences
- Title:
- Neighborhood Effects: Social Environment
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- Creator:
- Reference USA, City of Detroit, ESRI, Data Driven Detroit, and Veinot, Tiffany C.
- Description:
- Active living resources include spaces and organizations that facilitate physical activity, including 1) park land, 2) recreation areas (including parks, golf courses, amusement parks, beaches and other recreational landmarks); and 3) recreation centers (including gyms, dancing instruction, martial arts instruction, bowling centers, yoga instruction, sports clubs, fitness programs, golf course, pilates instruction, personal trainers, swimming pools, skating rinks, etc.) Coverage for all data: 10-county Detroit-Warren-Ann Arbor Combined Statistical Area.
- Keyword:
- Recreation Areas, Park Land, Census tract level, Metropolitan Detroit, Spatial Measures, Recreation Centers, and Michigan
- Citation to related publication:
- Discipline:
- Health Sciences, Other, and Social Sciences
- Title:
- Neighborhood Effects Active Living Resources
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- Creator:
- Wellman, Michael P.
- Description:
- For each game: - file in JSON format with raw payoff data - text file with game-theoretic analysis results
- Citation to related publication:
- Discipline:
- Social Sciences
- Title:
- Data Supplement: Self-Confirming Price-Prediction Strategies for Simultaneous One-Shot Auctions
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- Creator:
- Data Driven Detroit, Yan, Xiang (Jacob), Okullo, Dolorence, Gomez-Lopez, Iris N., Veinot, Tiffany C., and Goodspeed, Robert
- Description:
- The food environment is: 1) The physical presence of food that affects a person’s diet; 2) A person’s proximity to food store locations; 3) The distribution of food stores, food service, and any physical entity by which food may be obtained; or 4) A connected system that allows access to food. (Source: https://www.cdc.gov/healthyplaces/healthtopics/healthyfood/general.htm) Data included here concern: 1) Food access; and 2) Liquor access. Spatial Coverage for most data: 10-county Detroit-Warren-Ann Arbor Combined Statistical Area, Michigan, USA. See exception for grocery store data below.
- Keyword:
- Food Deserts, Census tract level, Full-Line Grocery Stores, Modified Retail Food Environment Index (MRFEI), Farmer’s Markets, Spatial Measures, and Fast Food Establishments
- Citation to related publication:
- Discipline:
- Health Sciences, Other, and Social Sciences
- Title:
- Neighborhood Effects: Food Environment
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- Creator:
- Gomez-Lopez, Iris N., Goodspeed, Robert, Reddy, Shruthi, Clarke, Phillipa J., Okullo, Dolorence, Veinot, Tiffany C, and Data Driven Detroit
- Description:
- The information and education environment refers to: 1) the presence of information infrastructures such as broadband Internet access and public libraries in a location; 2) a person’s proximity to information infrastructures and sources; 3) the distribution of information infrastructures, sources and in a specific location; and 4) exposure to specific messages (information content) within a specific location. Coverage for all data: 10-county Detroit-Warren-Ann Arbor Combined Statistical Area.
- Keyword:
- Residential Broadband Data Adoption Rates, Census tract level, Broadband Internet Access and Speed, Colleges and Universities, Public Libraries, Spatial Measures, and Schools
- Citation to related publication:
- Discipline:
- Science, Health Sciences, and Social Sciences
- Title:
- Neighborhood effects : Information and Education Environment
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- Creator:
- Schulte, Erica M
- Description:
- The data set supports a study investigating which foods may be most implicated in addictive-like eating by examining how nutritionally diverse foods relate to loss of control consumption and various subjective effect reports. Participants (n = 501) self-reported how likely they were to experience a loss of control over their consumption of 30 nutritionally diverse foods and rated each food on five subjective effect report questions that assess the abuse liability of substances (liking, pleasure, craving, averseness, intensity). Hierarchical cluster analytic techniques were used to examine how foods grouped together based on each question. Highly processed foods, with added fats and/or refined carbohydrates, clustered together and were associated with greater loss of control, liking, pleasure, and craving. The clusters yielded from the subjective effect reports assessing liking, pleasure, and craving were most similar to clusters formed based on loss of control over consumption, whereas the clusters yielded from averseness and intensity did not meaningfully differentiate food items. The associated study applies methodology used to assess the abuse liability of substances to understand whether foods may vary in their potential to be associated with addictive-like consumption. Highly processed foods (e.g., pizza, chocolate) appear to be most related to an indicator of addictive-like eating (loss of control) and several subjective effect reports (liking, pleasure, craving). Thus, these foods may be particularly reinforcing and capable of triggering an addictive-like response in some individuals. Future research is warranted to understand whether highly processed foods are related to these indicators of abuse liability at a similar magnitude as addictive substances. The data set is presented in both .sav format for use with SPSS software and in csv format.
- Keyword:
- Behavioral Addiction and Food Consumption
- Citation to related publication:
- Schulte EM, Smeal JK, Gearhardt AN (2017) Foods are differentially associated with subjective effect report questions of abuse liability. PLoS ONE 12(8): e0184220. https://doi.org/10.1371/journal.pone.0184220
- Discipline:
- Social Sciences
- Title:
- Subjective Effect Reports of Food
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- Creator:
- Beck, Jess
- Description:
- These data include skeletal and dental inventories, assessments of skeletal and dental pathology, and the age and sex of individuals buried at Necropolis 1, Necropolis 2, and Necropolis 4 at the Copper Age site of Marroquíes Bajos. They are shared here in accordance with the NSF Data Management Plan associated with Doctoral Dissertation Improvement Grant BCS-1440017.
- Keyword:
- Iberia, Archaeology, Copper Age, and Bioarchaeology
- Citation to related publication:
- Discipline:
- Social Sciences
- Title:
- Marroquíes Bajos Bioarchaeological Project
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