Application of Sentiment Analysis Algorithm based on Big Data in Mental Health Assessment

Nowadays, college students are under increasing pressure. The accumulation of various pressures not only brings great harm to human body, but also brings many mental health (MH) problems. In this paper, large-scale Internet big data is taken as the research object, and the data mining algorithm based on heuristic clustering is studied. After text clustering, an evaluation index system based on text set is constructed based on the corresponding index of text set. The first-level evaluation indicators include emotional adjustment, learning influence, life influence and career influence. Using this model to evaluate the MH of college students can cluster the MH indicators of college students well in a large number of data, and the false positive rate and the false negative rate will not exceed 1%. This paper is helpful to the harmonious development of college students' MH.