Twitter Sentiment Geographical Index

Introduction​ Promoting well-being is one of the key targets of Sustainable Development Goals at the United Nations. Many governments worldwide are incorporating subjective well-being (SWB) indicators to complement traditional objective and economic metrics. Our Twitter Sentiment Geographical Index (TSGI) can provide a high granularity monitor of well-being worldwide. This dataset is a joint effort of the Sustainable Urbanization Lab at MIT and Center for Geographic Analysis at Harvard. ===== ===== ===== ===== ===== ===== ===== ===== ===== ===== ===== ===== Granularity Geographical granularity: We provide a sentiment index on four levels: Globe, Country, State/Province, County/City Temporal granularity: The data covers 2012 to the present. And we update the sentiment data on a monthly basis. ===== ===== ===== ===== ===== ===== ===== ===== ===== ===== ===== ===== Fields DATE---- date ---- the date of the sentiment index NAME_0 ---- string ---- the country name NAME_1 ---- string ---- the state/province name NAME_2 ---- string ---- the county/city name SCORE ---- float ---- a float value between 0 and 1 representing the sentiment index where 1 represents a positive sentiment and 0 represents the negative sentiment. N ---- int ---- the number of posts generated given the specific date ===== ===== ===== ===== ===== ===== ===== ===== ===== ===== ===== ===== Citation rule If you use the TSGI in your research, please cite it as below: \"Twitter Sentiment Geographical Index (https://doi.org/10.7910/DVN/3IL00Q)\" ===== ===== ===== ===== ===== ===== ===== ===== ===== ===== ===== ===== Additional information For more information regarding the source dataset, please visit: here This dataset is free of usage for academic purposes. Please contact us should you have any questions or other usage cases. Thanks!