A social matching system for an online dating network : a preliminary study

Due to the change in attitudes and lifestyles, people expect to find new partners and friends via various ways now-a-days. Online dating networks create a network for people to meet each other and allow making contact with different objectives of developing a personal, romantic or sexual relationship. Due to the higher expectation of users, online matching companies are trying to adopt recommender systems. However, the existing recommendation techniques such as content-based, collaborative filtering or hybrid techniques focus on users explicit contact behaviors but ignore the implicit relationship among users in the network. This paper proposes a social matching system that uses past relations and user similarities in finding potential matches. The proposed system is evaluated on the dataset collected from an online dating network. Empirical analysis shows that the recommendation success rate has increased to 31% as compared to the baseline success rate of 19%.

Social network analysis of an online dating network

Online social networks can be found everywhere from chatting websites like MSN, blogs such as MySpace to social media such as YouTube and second life. Among them, there is one interesting type of online social networks, online dating network that is growing fast. This paper analyzes an online dating network from social network analysis point of view. Observations are made and results are obtained in order to suggest a better recommendation system for people-to-people networks.

A social matching system : using implicit and explicit information for personalized recommendation in online dating service

Online dating websites enable a specific form of social networking and their efficiency can be increased by supporting proactive recommendations based on participants' preferences with the use of data mining. This research develops two-way recommendation methods for people-to-people recommendation for large online social networks such as online dating networks. This research discovers the characteristics of the online dating networks and utilises these characteristics in developing efficient people-to-people recommendation methods. Methods developed support improved recommendation accuracy, can handle data sparsity that often comes with large data sets and are scalable for handling online networks with a large number of users.

A recommendation method for online dating networks based on social relations and demographic information

A new relationship type of social networks - online dating - are gaining popularity. With a large member base, users of a dating network are overloaded with choices about their ideal partners. Recommendation methods can be utilized to overcome this problem. However, traditional recommendation methods do not work effectively for online dating networks where the dataset is sparse and large, and a two-way matching is required. This paper applies social networking concepts to solve the problem of developing a recommendation method for online dating networks. We propose a method by using clustering, SimRank and adapted SimRank algorithms to recommend matching candidates. Empirical results show that the proposed method can achieve nearly double the performance of the traditional collaborative filtering and common neighbor methods of recommendation.

The economies within an online social network market : A case study of Ravelry

The capacity of the internet to handle micro-transactions and to cater to niche markets is a boon for some areas of the creative industries, which have always been associated with smallscale micro business activities. This paper looks at the specific case of the specialist Social Networking Site Ravelry: a site for knitters, crocheters, spinners and dyers. It traces the interactions between amateurs and professionals through the emergence of social networking sites. An analytic framework of social network markets (see Potts, Cunningham, Hartley and Omerod, 2008) is employed to allow for the inclusion of amateur, social, semi-professional,professional and institutional actors within a networked sphere of activity, rather than excluding some of these actors as outside of recognised value-production. The reliance on social networks to determine the economic success of design, production and consumption is exemplified in this small scale example. This paper eschews the dichotomy of commercial and non-commercial by bringing to the fore the hybridity of this site where financial and social economies co-exist.

Dating and intimacy in the 21st century : the use of online dating sites in Australia

This article examines the growing phenomenon of online dating and intimacy in the 21st century. The exponential rise of communications technologies, which is both reflective and constitutive of an increasingly networked and globalized society, has the potential to significantly influence the nature of intimacy in everyday life. Yet, to date, there has been a minimal response by sociologists to seek, describe and understand this influence. In this article, we present some of the key findings of our research on online dating in Australia, in order to foster a debate about the sociological impacts on intimacy in the postmodern world. Based on a web audit of more than 60 online dating sites and in-depth interviews with 23 users of online dating services, we argue that recent global trends are influencing the uptake of online technologies for the purposes of forming intimate relations. Further, some of the mediating effects of these technologies – in particular, the hypercommunication – may have specific implications for the nature of intimacy in the global era.

Improving matching process in social network

Online dating networks, a type of social network, are gaining popularity. With many people joining and being available in the network, users are overwhelmed with choices when choosing their ideal partners. This problem can be overcome by utilizing recommendation methods. However, traditional recommendation methods are ineffective and inefficient for online dating networks where the dataset is sparse and/or large and two-way matching is required. We propose a methodology by using clustering, SimRank to recommend matching candidates to users in an online dating network. Data from a live online dating network is used in evaluation. The success rate of recommendation obtained using the proposed method is compared with baseline success rate of the network and the performance is improved by double.

Online dating and intimacy in a mobile world

The nature and possibilities for intimacy between adults are changing in the mobile era. Bauman (2003) has decreed this the era of ‘liquid love’, in which intimacy is commodified and committed relationships have been replaced by fleeting connections. In contrast, Giddens (1991; 1993) suggests that the reordering of everyday life in late-stage modernity has given rise to the possibility of a democratization of interpersonal interaction, characterized by reflexive ‘pure relationships’. The purpose of this paper is to consider theoretical debates about intimacy in the mobile era with regard to the contemporary practice of online dating. Drawing on our qualitative research with 23 online daters in Australia, we argue that, while the architecture of online dating is consistent with liquid love, many online daters simultaneously desire the possibilities for consumption afforded by liquid love, while aspiring to the formation of pure relationships and/or more practical forms of caring. This creates tensions in people’s experiences of this form of purposeful meeting, which are reflective of the conflicting socialities of intimacy available to us in the mobile era. At the same time, our research revealed disruptions to these tensions, by illuminating experiences where the consumerist orientation of online dating stimulated processes of reflexive self-discovery amongst our participants.

A rule-based hybrid method for anomaly detection in online-social-network graphs

Detecting anomalies in the online social network is a significant task as it assists in revealing the useful and interesting information about the user behavior on the network. This paper proposes a rule-based hybrid method using graph theory, Fuzzy clustering and Fuzzy rules for modeling user relationships inherent in online-social-network and for identifying anomalies. Fuzzy C-Means clustering is used to cluster the data and Fuzzy inference engine is used to generate rules based on the cluster behavior. The proposed method is able to achieve improved accuracy for identifying anomalies in comparison to existing methods.

Matching and sorting in online dating

Using data on user attributes and interactions from an online dating site, we estimate mate preferences, and use the Gale-Shapley algorithm to predict stable matches. The predicted matches are similar to the actual matches achieved by the dating site, and the actual matches are approximately efficient. Out-of-sample predictions of offline matches, i.e., marriages, exhibit assortative mating patterns similar to those observed in actual marriages. Thus, mate preferences, without resort to search frictions, can generate sorting in marriages. However, we underpredict some of the correlation patterns; search frictions may play a role in explaining the discrepancy.

The Online dating romance scam: The psychological impact on victims – both financial and non-financial

This paper examined the psychological impact of the online dating romance scam. Unlike other mass-marketing fraud victims, these victims experienced a ‘double hit’ of the scam: a financial loss and the loss of a relationship. For most, the loss of the relationship was more upsetting than their financial losses (many described the loss of the relationship as a ‘death’). Some described their experience as traumatic and all were affected negatively by the crime. Most victims had not found ways to cope given the lack of understanding from family and friends. Denial (e.g., not accepting the scam was real or not being able to separate the fake identity with the criminal) was identified as an ineffective means of coping, leaving the victim vulnerable to a second wave of the scam. Suggestions are made as to how to change policy with regards to law enforcement deal with this crime.

The Hidden Truths of Self-Presentation, Self-Disclosure, and Deception on Online Dating Profiles: A Call for Change

The way in which individuals seek romantic partners has changed considerably in the past decades, most notably through online dating sites (ODSs). Despite the possibility of misrepresentation amongst client users, such sites continue to grow in popularity because ODSs provide a large pool from which individuals can select and attract potential partners. While much research has been undertaken on ODSs, little empirical research has examined postsecondary students’ use of ODSs. Therefore, this study sought to investigate why postsecondary students have become involved with and how they present themselves on ODSs. The researcher surveyed 20 postsecondary students and conducted in-depth interviews with 2 participants who use ODSs. Although the limited sample prevented results from being generalized, quantitative and qualitative analyses suggest that participants became involved with ODSs for various purposes, such as seeking long-term relationships and/or marriage partners, or simply exploring or visiting ODSs out of curiosity. Findings indicate that ODS users’ physical appearance and/or “attractiveness” is considered the strongest predictor of relationship success. The study discusses how participants’ self-presentation affects outcomes of ODS usage, particularly when negative self-identification and presentation corresponding to factors such as individuals’ weight and age are taken into account.

Why participate in an online social network: an empirical analysis

Despite their enormous success the motivation behind user participation in Online Social Networks is still little understood. This study explores a variety of possible incentives and provides an empirical evaluation of their subjective relevance. The analysis is based on survey data from 129 test subjects. Using Structural Equation Modeling, we identified that the satisfaction of the needs for belongingness and the esteem needs through self-presentation together with peer pressure are the main drivers of participation. The analysis of a sub-sample of active users pointed out the satisfaction of the cognitive needs as an additional participation determinant. Based on these findings, recommendations for online social network providers are made.