基于网页浏览内容的心理健康预测模型的研究
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摘要
目前,世界各地的人们都饱受心理健康问题所带来的困扰,这为心理健康问题预防工作带来了新的挑战.如果心理健康状态可以利用网页浏览内容进行预测,就可以为心理健康问题预防工作开辟新的方向.本文探讨了利用用户的网页浏览内容预测其心理健康状态的可行性,并使用支持向量机建立了基于网页浏览内容的心理健康预测模型.为了验证该算法模型的有效性,我们与另外两种算法模型的预测结果进行了对比,结果表明,基于支持向量机的算法模型能够更加有效地预测用户的心理健康状态.
At present, people around the world are suffering from mental health problems, which bring new challenges to the prevention of mental health problems. If mental health can be predicted using web browsing content, it can open up new directions for mental health prevention. In this paper, the feasibility of using the user's web browsing content to predict their mental health is discussed. A support vector machine is used to build a mental health prediction model based on web browsing content. In order to verify the effectiveness of the proposed algorithm, the results of comparison with the other two algorithms were compared. The results show that the algorithm model based on the support vector machine can more effectively predict the user's mental health status.
At present, people around the world are suffering from mental health problems, which bring new challenges to the prevention of mental health problems. If mental health can be predicted using web browsing content, it can open up new directions for mental health prevention. In this paper, the feasibility of using the user's web browsing content to predict their mental health is discussed. A support vector machine is used to build a mental health prediction model based on web browsing content. In order to verify the effectiveness of the proposed algorithm, the results of comparison with the other two algorithms were compared. The results show that the algorithm model based on the support vector machine can more effectively predict the user's mental health status.
引文
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[2]THOBABEN M.Mental health:a report of the surgeon general[J].Home Care Provider,2000,38(2):6-7.
[3]JR C P,MCCRAE R R.Influence of extraversion and neuroticism on subjective well-being:happy and unhappy people.[J].Journal of Personality&Social Psychology,1980,38(4):668-78.
[4]HIERONYMUS A N.Mental and physical health[J].Phi Delta Kappan,1950,31(9):446-447.
[5]STANLEY S,LAUGHARNE J.The impact of lifestyle factors on the physical health of people with a mental illness:a brief review[J].International Journal of Behavioral Medicine,2014,21(2):275-281.
[6]ROBSON D,GRAY R.Serious mental illness and physical health problems:a discussion paper[J].International Journal of Nursing Studies,2007,44(3):457-466.
[7]LOPEZ A D,MATHERS C D,EZZATI M,et al.Measuring the global burden of disease and risk factors,1990-2001[J].Theory and Applications of Special Functions,2006:448-57.
[8]LEE S,KLEINMAN A.Mental illness and social change in China[J].Harvard Review of Psychiatry,1997,5(1):43-46.
[9]欧阳文珍.嫉妒心理及其内隐性研究[J].心理科学,2000,23(4):63-66+128.
[10]王丽.基于神经网络的研究生心理健康状况预测分析[D].西安:西安科技大学,2016.
[11]张磊.社交网络用户的心理预测与心理信息应用[D].济南:济南大学,2015.
[12]田玮,朱廷劭.基于深度学习的微博用户自杀风险预测[J].中国科学院大学学报,2018,35(1):131-136.
[13]ZHU C,LI B,LI A,et al.Predicting depression from internet behaviors by time-frequency features[C]//Ieee/wic/acm International Conference on Web Intelligence.IEEE,2017:383-390.
[14]NIE D,GUAN Z,HAO B,et al.Predicting personality on social media with semi-supervised learning[C]//Ieee/wic/acm International Joint Conferences on Web Intelligence.IEEE,2014:158-165.
[15]GAO Y,LI H,ZHU T.Predicting subjective well-being by smartphone usage behaviors[C]//International Conference on Health Informatics.2014:317-322.
[16]BAI S,HAO B,LI A,et al.Predicting big five personality traits of microblog users[C]//Ieee/wic/acm International Joint Conferences on Web Intelligence.IEEE,2013:501-508.
[17]ZHU T,NING Y,LI A,et al.Using decision tree to predict mental health status based on web behavior[C]//2011 3rd Sympoisum on web society,2011:27-31.
[18]XU X,ZHU T,ZHANG R,et al.Pervasive mental health self-help based on cognitive-behavior therapy and machine learning[C]//International Conference on Pervasive Computing and Applications.IEEE,2011:212-219.
[19]BAI S,NING Y,YUAN S,et al.Predicting reader’s emotion on chinese web news articles[C]//International Conference on Pervasive Computing and the Networked World.Springer-Verlag,2012:16-27.
[20]ORQUIN J L.A Brunswik lens model of consumer health judgments of packaged foods[J].Journal of Consumer Behaviour,2014,13(4):270-281.
[21]Ajzen I.Residual effects of past on later behavior:habituation and reasoned action perspectives[J].Personality&Social Psychology Review,2002,6(2):107-122.
[22]ZHANG Q,ZHU Z H,ZHU T S,et al.Constructing the internet behavior ontology:projection from psychological phenomena with qualitative and quantitative methods[C]//International Conference on Active Media Technology.Springer-Verlag,2011:123-128.
[23]ZHANG F,ZHU T,LI A,et al.A survey of web behavior and mental health[C]//International Conference on Pervasive Computing and Applications.IEEE,2011:189-195.