Do You Feel Blue? Detection of Negative Feeling from Social Media

被引:7
|
作者
Polignano, Marco [1 ]
de Gemmis, Marco [1 ]
Narducci, Fedelucio [1 ]
Semeraro, Giovanni [1 ]
机构
[1] Univ Bari Aldo Moro, Dept Comp Sci, Via Edoardo Orabona 4, Bari, Italy
来源
AI*IA 2017 ADVANCES IN ARTIFICIAL INTELLIGENCE | 2017年 / 10640卷
关键词
Natural Language Processing; Emotion; Text annotation; Word embedding; Social media; User modeling; DEPRESSION;
D O I
10.1007/978-3-319-70169-1_24
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The blue feeling is the sensation which affects people when they feel down, depressed, sad and more generally when they are in a bad feeling state. In some cases, it is a recurring situation in their everyday life and it can be the first symptom of more complex psychological diseases such as depression. In the last decade, as consequence of the quick increase of detected cases of depression in children and teenagers, it has become very important to find strategies for a timely detection of this pathology. In this work, we describe a model that can support the detection task, by identifying some warning scenarios of blue feeling. The proposed architecture is composed by modules focused on different aspects that characterize the scenario: changes in heart rate, reduction of sleep, reduction of activities performed, increases of use of negative phrases and words. In particular, in this paper, we describe the approach adopted to analyze users posts on social media networks (SMNs) by using natural language processing techniques. The proposed approach is evaluated through an experimental session over a dataset of Facebook posts. The results show good performance in the detection of negative feeling.
引用
收藏
页码:321 / 333
页数:13
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