Literature DB >> 30706061

Twitter Health Surveillance (THS) System.

Manuel Rodríguez-Martínez1, Cristian C Garzón-Alfonso2.   

Abstract

We present the Twitter Health Surveillance (THS) application framework. THS is designed as an integrated platform to help health officials collect tweets, determine if they are related with a medical condition, extract metadata out of them, and create a big data warehouse that can be used to further analyze the data. THS is built atop open source tools and provides the following value added services: Data Acquisition, Tweet Classification, and Big Data Warehousing. In order to validate THS, we have created a collection of roughly twelve thousands labelled tweets. These tweets contain one or more target medical terms, and the labels indicate if the tweet is related or not to a medical condition. We used this collection to test various models based on LSTM and GRU recurrent neural networks. Our experiments show that we can classify tweets with 96% precision, 92% recall, and 91% F1 score. These results compare favorably with recent research on this area, and show the promise of our THS system.

Entities:  

Keywords:  Twitter; big data analytics; deep learning; disease detection; streaming

Year:  2019        PMID: 30706061      PMCID: PMC6350799          DOI: 10.1109/BigData.2018.8622504

Source DB:  PubMed          Journal:  Proc IEEE Int Conf Big Data


  3 in total

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3.  Evolutionary clustering and community detection algorithms for social media health surveillance.

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4.  JUE Insight: The geographic spread of COVID-19 correlates with the structure of social networks as measured by Facebook.

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  4 in total

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