Profiling Attitudes for Personalized Information Provision

PAROS is a generic system under design whose goal is to offer personalization, recommendation, and other adaptation services to information providing systems. In its heart lies a rich user model able to capture several diverse aspects of user behavior, interests, preferences, and other attitudes. The user model is instantiated with profiles of users, which are obtained by analyzing and appropriately interpreting potentially arbitrary pieces of user-relevant information coming from diverse sources. These profiles are maintained by the system, updated incrementally as additional data on users becomes available, and used by a variety of information systems to adapt the functionality to the users’ characteristics

Wearing Many (Social) Hats: How Different are Your Different Social Network Personae?

This paper investigates when users create profiles in different social networks, whether they are redundant expressions of the same persona, or they are adapted to each platform. Using the personal webpages of 116,998 users on About.me, we identify and extract matched user profiles on several major social networks including Facebook, Twitter, LinkedIn, and Instagram. We find evidence for distinct site-specific norms, such as differences in the language used in the text of the profile self-description, and the kind of picture used as profile image. By learning a model that robustly identifies the platform given a user's profile image (0.657--0.829 AUC) or self-description (0.608--0.847 AUC), we confirm that users do adapt their behaviour to individual platforms in an identifiable and learnable manner. However, different genders and age groups adapt their behaviour differently from each other, and these differences are, in general, consistent across different platforms. We show that differences in social profile construction correspond to differences in how formal or informal the platform is.Comment: Accepted at the 11th International AAAI Conference on Web and Social Media (ICWSM17

Psychological elements explaining the consumer's adoption and use of a website recommendation system: A theoretical framework proposal

The purpose of this paper is to understand, with an emphasis on the psychological perspective of the research problem, the consumer's adoption and use of a certain web site recommendation system as well as the main psychological outcomes involved. The approach takes the form of theoretical modelling. Findings: A conceptual model is proposed and discussed. A total of 20 research propositions are theoretically analyzed and justified. Research limitations/implications: The theoretical discussion developed here is not empirically validated. This represents an opportunity for future research. Practical implications: The ideas extracted from the discussion of the conceptual model should be a help for recommendation systems designers and web site managers, so that they may be more aware, when working with such systems, of the psychological process consumers undergo when interacting with them. In this regard, numerous practical reflections and suggestions are presented

Towards Psychometrics-based Friend Recommendations in Social Networking Services

Two of the defining elements of Social Networking Services are the social profile, containing information about the user, and the social graph, containing information about the connections between users. Social Networking Services are used to connect to known people as well as to discover new contacts. Current friend recommendation mechanisms typically utilize the social graph. In this paper, we argue that psychometrics, the field of measuring personality traits, can help make meaningful friend recommendations based on an extended social profile containing collected smartphone sensor data. This will support the development of highly distributed Social Networking Services without central knowledge of the social graph.Comment: Accepted for publication at the 2017 International Conference on AI & Mobile Services (IEEE AIMS

Sensing Subjective Well-being from Social Media

Subjective Well-being(SWB), which refers to how people experience the quality of their lives, is of great use to public policy-makers as well as economic, sociological research, etc. Traditionally, the measurement of SWB relies on time-consuming and costly self-report questionnaires. Nowadays, people are motivated to share their experiences and feelings on social media, so we propose to sense SWB from the vast user generated data on social media. By utilizing 1785 users' social media data with SWB labels, we train machine learning models that are able to "sense" individual SWB from users' social media. Our model, which attains the state-by-art prediction accuracy, can then be used to identify SWB of large population of social media users in time with very low cost.Comment: 12 pages, 1 figures, 2 tables, 10th International Conference, AMT 2014, Warsaw, Poland, August 11-14, 2014. Proceeding

Harm-reduction approaches for self-cutting in inpatient mental health settings:development and preliminary validation of the Attitudes to Self-cutting Management (ASc-Me) Scale

IntroductionHarm-reduction approaches for self-harm in mental health settings have been under-researched.AimTo develop a measure of the acceptability of management approaches for self-cutting in mental health inpatient settings.MethodsStage one: scale items were generated from relevant literature and staff/service user consultation. Stage two: A cross-sectional survey and statistical methods from classical test theory informed scale development.Results/FindingsAt stage one N=27 staff and service users participated. At stage two N=215 people (n=175 current mental health practitioners and n=40 people with experience of self-cutting as a UK mental health inpatient) completed surveys. Principal components analysis revealed a simple factor structure such that each method had a unique acceptability profile. Reliability, construct validity, and internal consistency were acceptable. The harm-reduction approaches 'advising on wound-care' and 'providing a first aid kit' were broadly endorsed; 'providing sterile razors' and 'maintaining a supportive nursing presence during cutting' were less acceptable but more so than seclusion and restraint.DiscussionThe Attitudes to Self-cutting Management scale is a reliable and valid measure that could inform service design and development.Implications for practiceNurses should discuss different options for management of self-cutting with service users. Harm reduction approaches may be more acceptable than coercive measures. This article is protected by copyright. All rights reserved.</p