抑郁在线人物角色分类的社会挖掘交叉评价。

IF 1.5 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Alina Trifan, José Luis Oliveira
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引用次数: 2

摘要

随着社交网络使用的不断增加,社交挖掘正在稳步成为数字表型的一个强大组成部分。在本文中,我们探索了社交挖掘,将Reddit的自诊断抑郁用户分类为社交网络。为了了解当数据源几乎相同时迁移学习的影响,我们基于两个公共数据集进行了交叉评估研究。我们进一步补充这些结果与迁移学习在产后抑郁症分类的实验,使用语料库我们已经收集的问题。我们的研究结果表明,社会挖掘中的迁移学习可能仍处于计算研究的早期阶段,我们深入讨论了其含义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cross-evaluation of social mining for classification of depressed online personas.

With the continuous increase in the use of social networks, social mining is steadily becoming a powerful component of digital phenotyping. In this paper we explore social mining for the classification of self-diagnosed depressed users of Reddit as social network. We conduct a cross evaluation study based on two public datasets in order to understand the impact of transfer learning when the data source is virtually the same. We further complement these results with an experiment of transfer learning in post-partum depression classification, using a corpus we have collected for the matter. Our findings show that transfer learning in social mining might still be at an early stage in computational research and we thoroughly discuss its implications.

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来源期刊
Journal of Integrative Bioinformatics
Journal of Integrative Bioinformatics Medicine-Medicine (all)
CiteScore
3.10
自引率
5.30%
发文量
27
审稿时长
12 weeks
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