使用梯度方法预测推特用户的心理健康，包括COVID-19的增长模式和推文

2020 IEEE International Conference on Humanized Computing and Communication with Artificial Intelligence (HCCAI) Pub Date : 2020-09-01 DOI:10.1109/HCCAI49649.2020.00017

Sudha Tushara Sadasivuni, Yanqing Zhang

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引用次数: 4

摘要

推特用户发布推特来表达他们的感受、情绪和行为。在2019冠状病毒病期间，人们的生活习惯发生了变化。这种日常生活的变化影响了人们的心理健康。我们通过推特用户在这段时间内的推文研究了他们的心理健康状况，并将其与COVID-19的增长模式进行了比较。我们还尝试预测抑郁推文，并使用ARIMA方法将其与真实数据进行比较。我们发现，我们对推特的观察和世卫组织的COVID-19疫情报告也遵循类似的模式。我们使用ARIMA方法的预测结果支持实际数据。

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Using Gradient Methods to Predict Twitter Users' Mental Health with Both COVID-19 Growth Patterns and Tweets

Twitter users post tweets to express their feelings, emotions, and behavior. During COVID-19 times, people moved to varied life routines. Such a change in daily life affected people's mental health. We studied the mental health of twitter users during this time through their tweets and compared them with the COVID-19 growth pattern. We also attempted to forecast the depressive tweets and compared them with real data using ARIMA methods. We found our observations of tweets and COVID-19 Epidemic reports of WHO followed a similar pattern. Our forecast findings with ARIMA methods supported the real data.

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2020 IEEE International Conference on Humanized Computing and Communication with Artificial Intelligence (HCCAI)

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