{"title":"从推特分析意大利居民天气与情绪的相关性","authors":"G. Modoni, Davide Tosi","doi":"10.1109/W-FiCloud.2016.53","DOIUrl":null,"url":null,"abstract":"In the last years there has been a strong interest in the aggregated data extracted from social networks such as Twitter, Facebook or Instagram, whose contents provide streams of information about the users' behavior. Analyzing these large data sets reveals trends that can be utilized in various fields. An interesting field of application of these data is presented in this paper, which illustrates an approach to perform a psycholinguistic analysis of the Twitter contents written in Italian language by Italy residents. In this way the predisposition of the latter to mental disorders such as the depression can be in particular measured. Moreover, the results of this analysis can be then correlated with the conditions of the weather in order to understand whether the correlation between weather and health is a common cliché or it can be demonstrated in some way e.g. through a mathematical relationship.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Correlation of Weather and Moods of the Italy Residents through an Analysis of Their Tweets\",\"authors\":\"G. Modoni, Davide Tosi\",\"doi\":\"10.1109/W-FiCloud.2016.53\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the last years there has been a strong interest in the aggregated data extracted from social networks such as Twitter, Facebook or Instagram, whose contents provide streams of information about the users' behavior. Analyzing these large data sets reveals trends that can be utilized in various fields. An interesting field of application of these data is presented in this paper, which illustrates an approach to perform a psycholinguistic analysis of the Twitter contents written in Italian language by Italy residents. In this way the predisposition of the latter to mental disorders such as the depression can be in particular measured. Moreover, the results of this analysis can be then correlated with the conditions of the weather in order to understand whether the correlation between weather and health is a common cliché or it can be demonstrated in some way e.g. through a mathematical relationship.\",\"PeriodicalId\":441441,\"journal\":{\"name\":\"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)\",\"volume\":\"65 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/W-FiCloud.2016.53\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/W-FiCloud.2016.53","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Correlation of Weather and Moods of the Italy Residents through an Analysis of Their Tweets
In the last years there has been a strong interest in the aggregated data extracted from social networks such as Twitter, Facebook or Instagram, whose contents provide streams of information about the users' behavior. Analyzing these large data sets reveals trends that can be utilized in various fields. An interesting field of application of these data is presented in this paper, which illustrates an approach to perform a psycholinguistic analysis of the Twitter contents written in Italian language by Italy residents. In this way the predisposition of the latter to mental disorders such as the depression can be in particular measured. Moreover, the results of this analysis can be then correlated with the conditions of the weather in order to understand whether the correlation between weather and health is a common cliché or it can be demonstrated in some way e.g. through a mathematical relationship.