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MOESM2 of Uncovering the relationships between military community health and affects expressed in social media

NIAID Data Ecosystem2026-03-10 收录

数据链接：

https://figshare.com/articles/dataset/MOESM2_of_Uncovering_the_relationships_between_military_community_health_and_affects_expressed_in_social_media/5096674 数据链接链接失效反馈

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Availability of data and materials. (zip)

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创建时间：

2017-06-09

军人心理健康

战后心理适应

After a full-scale armed conflict, tens of thousands of service members, including professional warfighters and reservists, return home facing an increased risk of PTSD and other mental disorders, as

DataCite Commons2026-02-24 更新100

Datasets details.

社交媒体情感

仇恨言论检测

Sentiment analysis is a pivotal domain in Natural Language Processing (NLP), particularly for understanding opinions expressed in sequential and textual data with the usage of machine learning. It inv

NIAID Data Ecosystem50

Characteristics of individuals who left the UKAF and who had contact with mental health services in the 12 months prior to suicide and matched controls who had not served in the UKAF.

军人心理健康

自杀风险分析

Characteristics of individuals who left the UKAF and who had contact with mental health services in the 12 months prior to suicide and matched controls who had not served in the UKAF.

Figshare2023-08-08 更新40

Effekten af udstationering, 2011

军人心理健康

退伍军人社会适应

Undersøgelsen er bestilt af Soldaterlegatet, som er en selvstændig privat fond og udarbejdet af SFI Formålet er at måle, hvordan soldaternes psykiske og fysiske helbred bliver påvirket so

DataCite Commons2024-10-11 更新50

The average number of daily tweets (average #), together with the mean and standard deviation (s.d.) of tweetwise sentiment scores calculated from the RoBERTa method for different cities in different time periods.

社交媒体情感

城市情感趋势

The average number of daily tweets (average #), together with the mean and standard deviation (s.d.) of tweetwise sentiment scores calculated from the RoBERTa method for different cities in different

Figshare2023-02-24 更新40

MOESM2 of Uncovering the relationships between military community health and affects expressed in social media

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