基于“用户画像”的阅读疗法模式研究——以抑郁症为例

发布时间：2018-08-25 19:56

【摘要】：针对目前抑郁症阅读疗法施治对象的选取样本过于单一,私密性差,不能及时发现潜在患者,及时治疗的现状,提出了在大数据背景下基于"用户画像"的抑郁症阅读疗法新模式。该模式首先根据"伯恩斯抑郁症清单(BDC)"的内容来构造抑郁情绪的种子词,然后基于机器学习的方法,综合提炼用户网上行为和抑郁情绪的主观表露,构建用户抑郁情感词典。根据抑郁情感词典分析用户微博文本,计算其抑郁情感指数,得到"用户画像",进而推送相应的阅读治疗资源。基于"用户画像"的阅读疗法模式大大突破了受众范围,便于准确把握诊断、治疗时机,使患者在无意识状态下接受阅读治疗,减轻了患者经济和精神的双重压力,具有较高的社会价值和重要的现实意义。
[Abstract]:In view of the current situation that the selected sample of reading therapy for depression is too single, the privacy is poor, the potential patients can not be found in time, and the current situation of timely treatment. In this paper, a new reading therapy model of depression based on user portrait is proposed under the background of big data. The model firstly constructs the seed words of depression according to the contents of "Burns depression list (BDC)", and then, based on the method of machine learning, synthetically extracts the subjective expression of user's online behavior and depression emotion, and constructs the user's depression emotion dictionary. According to the depression emotion dictionary analysis user Weibo text, calculates its depression emotion index, obtains "the user portrait", then pushes the corresponding reading treatment resources. The reading therapy model based on "user Portrait" has greatly broken through the audience scope, is convenient to accurately grasp the diagnosis, the treatment opportunity, causes the patient to accept the reading treatment in the unconscious state, alleviates the patient's double pressure of economy and spirit. It has high social value and important practical significance.
【作者单位】：曲阜师范大学日照校区图书馆;曲阜师范大学信息科学与工程学院;
【基金】：2016年度校级哲学社会科学研究规划项目“新媒体环境下齐鲁传统文化经典藏读模式研究”(编号:XSK201615)的研究成果之一
【分类号】：G252.1;R749.41

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