Extracting Everyday Health Interests from Online Communities
نویسندگان
چکیده
Increasing numbers of patients are using online communities to seek support by posting personal stories and requesting information. To leverage this trend, we investigated Natural Language Processing (NLP) tools for extracting users’ health interests from online communities. We identified relevant semantic types of the Unified Medical Language System (UMLS) for online communities. The results suggest that we can repurpose NLP tools for online communities without losing critical information.
منابع مشابه
Health-Related Hot Topic Detection in Online Communities Using Text Clustering
Recently, health-related social media services, especially online health communities, have rapidly emerged. Patients with various health conditions participate in online health communities to share their experiences and exchange healthcare knowledge. Exploring hot topics in online health communities helps us better understand patients' needs and interest in health-related knowledge. However, th...
متن کاملIdentifying a Company's Non-Customer Online Communities: a Proto-typology
This paper describes an exploratory, qualitative study of a process for extracting, identifying and exploiting an enterprise's implicit (less visible) web communities using link analysis. By identifying the implicit communities' relationships to a specific enterprise, the information can be organized into stakeholder groups and used for 'listening' to the external environments. A prototypology ...
متن کاملKnowledge Discovery from Various Algorithms: A Survey
Text mining is nothing but extracting useful information from text. The information to be extracted is explicitly stated in the text. Text mining can be applied in various domains like medical, economical, etc. Medical text extraction can be done through medical patient reports, online medical journals, online health communities, etc. Text mining includes different tasks like classification, su...
متن کاملExtracting Communities of Interests for Semantics-based Graph Searches
We propose an algorithm that divides a graph, whose vertices are users and whose edges represent shared interests, into subgraphs communities of interests (COIs). Our algorithm differs from conventional modularity-based community extraction because it introduces a mechanism to harmonize the number of users in each COI. It also attaches semantic tags to the relationships between COIs or between ...
متن کاملPatterns of interaction and everyday knowledge sharing in social network environments
Our research explores online social networking sites to describe the patterns of participation and knowledge sharing in these spaces. We examine how knowledge is shared and how participation is potentially shaped by social or material resources of the space. Our presentation will focus on data gathered from two different types of social networking sites. Theoretical Background Educational resea...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2012