Recent US Census Data the American Community Survey,

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This dataset has been developed based on the work of the GeoCOV19Tweets Dataset. The original work by Lamsal, R. runs network analysis on a similar dataset to understand the underlying relationship between countries and hashtags. The work did an analysis on roughly 300k number of [country, hashtag] relations from 190 countries and territories, and 5055 unique hashtags.

Instructions: 

This dataset provides [place, hashtag] relationships in a Comma-separated values (CSV) file. Each line represents a relationship. You can simply use the CSV file as per your research needs.

However, if you need to change the place entity from city (currently the dataset uses ["place"]["name"] object) to country, you'll have to consider the ["place"]["country"] object instead. The sample script is provided with this dataset. The script takes in a list of tweet IDs present in a CSV file and hydrates the IDs to extract places and hashtags relationships. The script is written for twarc.

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Crowds express emotions as a collective individual, which is evident from the sounds that a crowd produces in particular events, e.g., collective booing, laughing or cheering in sports matches, movies, theaters, concerts, political demonstrations, and riots.

Instructions: 

Extract locally the zip files, read the readme file.

Instructions for dataset usage are included in the open access paper: Franzoni, V., Biondi, G., Milani, A., Emotional sounds of crowds: spectrogram-based analysis using deep learning (2020) Multimedia Tools and Applications, 79 (47-48), pp. 36063-36075. https://doi.org/10.1007/s11042-020-09428-x

File are released under Creative Commons Attribution-ShareAlike 4.0 International License

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Psychometric Data

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Social images analysis from social networks is considered as one of the most popular social technologies. Social images analysis is an active research topic in recent years and in order to promotes social images’s analysis research, the REGIM-Lab.: REsearch Groups in Intelligent Machines, ENIS, University of Sfax, Tunisia provides the SmartCityZen database’2016 freely of charge to social images analysis researchers.

Instructions: 

Download Zip file and extract it.

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Social images analysis from social networks is considered as one of the most popular social technologies. Social images analysis is an active research topic in recent years and in order to promotes social images’s analysis research, the REGIM-Lab.: REsearch Groups in Intelligent Machines, ENIS, University of Sfax, Tunisia provides the Sm@rtCityZen social images database freely of charge to social images analysis researchers.

Instructions: 

Download Zip file and extract it.

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109 Views

Data set of 26/11 Mumbai attack is based on Mumbai Terrorist Attacks 2008 India Ministry of External Affairs Dossier and News reports. 10 terrorist operated in India distributed in five sub-groups, simultaneously 3 other person comes in light as per report those were having in continue touch with these terrorist from Pakistan and giving them instructions.                                                                                  

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AI Ethics Global Document Collection Daniel Schiff, Jason Borenstein, Justin Biddle, & Kelly Laas Documents in the dataset were published between January 2016 through July 2019 This dataset is associated with a (forthcoming) paper in IEEE Transactions on Technology and Society, entitled "AI Ethics in the Public, Private, and NGO Sectors: A Review of a Global Document Collection.

Instructions: 

Instructions and Codebook are included in the first sheets of the dataset.

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AI Ethics Global Document Collection

Daniel Schiff, Jason Borenstein, Justin Biddle, & Kelly Laas

Documents in the dataset were published between January 2016 through July 2019

This dataset is associated with a (forthcoming) paper in IEEE Transactions on Technology and Society, entitled "AI Ethics in the Public, Private, and NGO Sectors: A Review of a Global Document Collection.

Instructions: 

Instructions and Codebook are included in the first sheets of the dataset.

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This dataset is a set of eighteen directed networks that represents message exchanges among Twitter accounts during eighteen crisis events. The dataset comprises 645,339 anonymized unique user IDs and 1,396,709 edges that are labeled with respect to Plutchik's basic emotions (anger, fear, sadness, disgust, joy, trust, anticipation, and surprise) or "neutral" (if a tweet conveys no emotion).

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