Social web mining and sentiment analysis for mental illness detection

社交媒体越来越受欢迎。如今，互联网用户发布、写博客、发推特等等，内容几乎无所不包，包括健康话题。这样的社区支持对大量主题的积极讨论，并且在过去十年中在Web上蓬勃发展。特别是，互联网用户报告他们的情绪，他们的活动，他们的社会互动和他们周围的所有事件。这些信息可以作为一个由个人组成的庞大的有机传感器网络，用于在人口规模上模拟公共卫生。在这个项目中，我们专注于心理健康的自动预测和分析模型。最近，研究人员已经证明，社交媒体可以用来检测抑郁症等情感障碍。我们的项目目标是开发自动方法来利用社交媒体发布的大量数据，并应用社交网络挖掘和情感分析方法来检测高危人群并监测人群的精神状态。我们将研究我们的预测模型的一个应用场景，该模型将用于识别在线社区中的高危个人。该模型也将被心理学家和精神病学家用来识别与重大精神疾病相关的变量。在这个项目中开发的算法可以适用于其他领域（例如，在高中生的背景下识别有风险的孩子或欺凌的受害者）。我们组织了一个国际小组（加拿大/法国），拥有自然语言处理、数据挖掘、社交媒体处理和医学信息学方面的专业知识。该联盟还包括心理学家，他们将专注于开发方法对医疗保健管理的影响。参与该项目的加拿大公司Girih Inc.将贡献其在社交媒体数据收集和此类数据抽样方面的经验。NSERC/ANR的联合呼吁为这个项目提供了一个完美的机会。此外，这两个小组以一种协同的方式为英语和法语提供计算网络社会挖掘专业知识，这在这类研究中是一种罕见的资产，因为目前大多数工作都只关注英语。

Social media are increasingly popular. Nowadays, Internet users are posting, blogging, tweeting and so on about almost everything, including health topics. Such communities support active discussions on a plethora of topics and have flourished on the Web over the past decade. In particular, Internet users report their mood, their activities, their social interactions and all the events around them. This information could be used as a vast organic sensor network composed of individuals for modelling public health at a population scale. In this project, we focus on automatic prediction and analysis models for mental health. Recently, researchers have shown that social media can be used to detect affective disorders such as depression. The objective of our project is to develop automatic methods to exploit the massive data issued from social media and to apply social web mining and sentiment analysis methods to detect at-risk people and monitor the mental state of population. We will investigate one application scenario for our predictive model which will be used to identify at-risk individuals in online communities. The model will also be used by psychologists and psychiatrists to identify variables related to major mental illness. The algorithms developed in this project can be adapted for other domains (e.g., to identify at-risk kids or victims of bulling in the context of high-school students). We have organised an international group (Canada/France) which has expertise in natural language processing, data mining, social media processing and medical informatics. This consortium also includes psychologists who will focus on the effects the developed methods can have on health care management. The Canadian company involved in the project, Girih Inc. will contribute with their experience with social media data collection and sampling for this kind of data. The joint call NSERC/ANR represents a perfect opportunity for this project. Furthermore, the two groups provide in a synergistic way computational web social mining expertise for both English and French, which is a rare asset in this type of research, as most current work focuses uniquely on English.