Stroke survivors and their families receive information and support on an individual basis from an online forum: descriptive analysis of a population of 2348 patients and qualitative study of a sample of participants.

OBJECTIVE: To describe the characteristics of participants of an online stroke forum, their reasons for posting in the forum and whether responses addressed users' needs. METHODS: Descriptive analysis of the population of 2004-2011 archives of Talkstroke, the online forum of the Stroke Association, and comparison with patients admitted to hospital with stroke (Sentinel Stroke National Audit Programme, SSNAP). Thematic analysis of posts from a sample of 59 participants representative of age at stroke and sex. SETTINGS: UK. MAIN OUTCOME MEASURES: Characteristics of participants: age, sex, survivor versus patient by third party, side of stroke (R, L), social class; (from the sample of 59 participants): level of disability, stroke type, classification of users' intents for writing a post in the forum, quantification of needs addressed by the forum, topics of discussion. PARTICIPANTS: 2348 participants (957 stroke survivors, 1391 patients with stroke talked about by third party). RESULTS: Patients of both sexes and from a wide range of ages at stroke (0 to 95 years) and degrees of disability were represented in the forum, although younger than the UK stroke population (mean age 52 years vs 77 years in SSNAP). Analysis of 841 posts showed that the main users' intents for writing in the forum were requests/offers of information and support (58%) and sharing own experiences of stroke (35%). Most information needs were around stroke-related physical impairments, understanding the cause of stroke and the potential for recovery. Up to 95% of the users' intents were met by the replies received. CONCLUSIONS: Patients' needs expressed in the online forum confirm and widen the evidence from traditional research studies, showing that such forums are a potential resource for studying needs in this population. The forum provided an opportunity for patients and families to give and receive advice and social support.This study was funded by a NIHR Academic Clinical Lectureship to Anna De Simoni. The Evelyn Trust funded Chantal Balasooriya-Smeekens’s work.This is the final published version. It first appeared at http://bmjopen.bmj.com/content/6/4/e010501.abstract

Profiles of social networking sites users in the Netherlands

Online social networking has become a reality and integral part of the daily personal, social and business life. The extraordinary increase of the user numbers of Social Networking Sites (SNS) and the rampant creation of online communities presents businesses with many challenges and opportunities. From the commercial perspective, the SNS are an interesting and promising field: online social networks are important sources of market intelligence and also offer interesting options for co-operation, networking and marketing. For SMEs especially the Social Networking Sites represent a simple and low cost solution for listening the customer’s voice, reaching potential customers and creating extensive business networks. This paper presents the results of a national survey mapping the demographic, social and behavioral characteristics of the Dutch users of SNS. The study identifies four different user profiles and proposes a segmentation framework as basis for better understanding the nature and behavior of the participants in online communities. The findings present new insights to marketing strategists eager to use the communication potential of such communities; the findings are also interesting for businesses willing to explore the potential of online networking as a low cost yet very efficient alternative to physical, traditional networking

Developing an AI-Powered Chatbot to Support the Administration of Middle and High School Cybersecurity Camps

Throughout the Internet, many chatbots have been deployed by various organizations to answer questions asked by customers. In recent years, we have been running cybersecurity summer camps for youth. Due to COVID-19, our in-person camp has been changed to virtual camps. As a result, we decided to develop a chatbot to reduce the number of emails, phone calls, as well as the human burden for answering the same or similar questions again and again based on questions we received from previous camps. This paper introduces our practical experience to implement an AI-powered chatbot for middle and high school cybersecurity camps using the Google Dialogflow platform

Online Health Communities as a resource for collective sensemaking for men who experience fertility difficulty

Online health communities (OHCs) are dedicated spaces where users discuss specific topics in an anonymous virtual and asynchronous environment. This space can be valuable for men who experience fertility difficulty by providing a safe environment for them to share information and advice to understand their condition and share their experiences. I present findings from our study investigating men’s use of online communities. 603 posts from OHCs were qualitatively analysed to understand how men use online health communities when they experience a fertility difficulty. We found that peer support within these communities facilitated men to navigate a process of collective sensemaking to understand and accept a “new normal” within their fertility prognosis

On the adoption of crowdsourcing for theory testing

This paper examines the possibilities of using the crowdsourcing strategy for theory testing. We first analyse the relationships between theory building and theory testing activities. Then, based on a systematic review of 248 papers published in MISQ, we characterise the intents and pat-tern systems of activities that have been used for theory testing. Finally, we ascertain which ac-tivities can be crowdsourced or not and pinpoint a set of pathways supporting partial and total crowdsourcing. The obtained results show that a large number of activities related to data gath-ering can be crowdsourced, and that a number of intents have viable pathways supporting par-tial crowdsourcing

Understanding and exploiting user intent in community question answering

A number of Community Question Answering (CQA) services have emerged and proliferated in the last decade. Typical examples include Yahoo! Answers, WikiAnswers, and also domain-specific forums like StackOverflow. These services help users obtain information from a community - a user can post his or her questions which may then be answered by other users. Such a paradigm of information seeking is particularly appealing when the question cannot be answered directly by Web search engines due to the unavailability of relevant online content. However, question submitted to a CQA service are often colloquial and ambiguous. An accurate understanding of the intent behind a question is important for satisfying the user's information need more effectively and efficiently. In this thesis, we analyse the intent of each question in CQA by classifying it into five dimensions, namely: subjectivity, locality, navigationality, procedurality, and causality. By making use of advanced machine learning techniques, such as Co-Training and PU-Learning, we are able to attain consistent and significant classification improvements over the state-of-the-art in this area. In addition to the textual features, a variety of metadata features (such as the category where the question was posted to) are used to model a user's intent, which in turn help the CQA service to perform better in finding similar questions, identifying relevant answers, and recommending the most relevant answerers. We validate the usefulness of user intent in two different CQA tasks. Our first application is question retrieval, where we present a hybrid approach which blends several language modelling techniques, namely, the classic (query-likelihood) language model, the state-of-the-art translation-based language model, and our proposed intent-based language model. Our second application is answer validation, where we present a two-stage model which first ranks similar questions by using our proposed hybrid approach, and then validates whether the answer of the top candidate can be served as an answer to a new question by leveraging sentiment analysis, query quality assessment, and search lists validation

Dumping the Closet Skeletons Online: Exploring the Guilty Information Disclosure Behavior on Social Media

Privacy issues on social media are becoming an increasing area of concern. Paradoxically, some netizens are actively divulging their privacy online. Noticeably, some information is specifically guilt-related, though confession online is considered irrational. This preliminary study strives to understand this guilty information disclosure behavior through a mixed-approach. Analyzing posts and comments in a confession forum on Reddit, we find that sex-related and recreation-related topics prevail. Our qualitative investigation produces a thematic model with 71 codes, 17 concepts, 4 frames, 3 categories, and 9 relationships, capturing the intents, content, influencers of this behavior, and the interactions among users. Our contribution relies on the investigation of this peculiar behavior to better understand people’s privacy behavior. Also, we render a sophisticated framework around guilt-inducing behaviors useful for future work. We also suggest it as a mixture of conformity and counter-conformity, a modern “technology of self” and a variant of Adaptive Cognitive Theory