Social Recommendation Based on Content and Trust

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014

Analysis and identification of spamming behaviors in Sina Weibo microblog

Spamming has been a widespread problem for social networks. In recent years there is an increasing interest in the analysis of anti-spamming for microblogs, such as Twitter. In this paper we present a systematic research on the analysis of spamming in Sina Weibo platform, which is currently a dominant microblogging service provider in China. Our research objectives are to understand the specific spamming behaviors in Sina Weibo and find approaches to identify and block spammers in Sina Weibo based on spamming behavior classifiers. To start with the analysis of spamming behaviors we devise several effective methods to collect a large set of spammer samples, including uses of proactive honeypots and crawlers, keywords based searching and buying spammer samples directly from online merchants. We processed the database associated with these spammer samples and interestingly we found three representative spamming behaviors: Aggressive advertising, repeated duplicate reposting and aggressive following. We extract various features and compare the behaviors of spammers and legitimate users with regard to these features. It is found that spamming behaviors and normal behaviors have distinct characteristics. Based on these findings we design an automatic online spammer identification system. Through tests with real data it is demonstrated that the system can effectively detect the spamming behaviors and identify spammers in Sina Weibo.

Connecting social media to e-commerce:cold-start product recommendation using microblogging information

In recent years, the boundaries between e-commerce and social networking have become increasingly blurred. Many e-commerce websites support the mechanism of social login where users can sign on the websites using their social network identities such as their Facebook or Twitter accounts. Users can also post their newly purchased products on microblogs with links to the e-commerce product web pages. In this paper, we propose a novel solution for cross-site cold-start product recommendation, which aims to recommend products from e-commerce websites to users at social networking sites in 'cold-start' situations, a problem which has rarely been explored before. A major challenge is how to leverage knowledge extracted from social networking sites for cross-site cold-start product recommendation. We propose to use the linked users across social networking sites and e-commerce websites (users who have social networking accounts and have made purchases on e-commerce websites) as a bridge to map users' social networking features to another feature representation for product recommendation. In specific, we propose learning both users' and products' feature representations (called user embeddings and product embeddings, respectively) from data collected from e-commerce websites using recurrent neural networks and then apply a modified gradient boosting trees method to transform users' social networking features into user embeddings. We then develop a feature-based matrix factorization approach which can leverage the learnt user embeddings for cold-start product recommendation. Experimental results on a large dataset constructed from the largest Chinese microblogging service Sina Weibo and the largest Chinese B2C e-commerce website JingDong have shown the effectiveness of our proposed framework.

Principal component analysis and assessment of language network activation patterns in pediatric epilepsy

This dissertation establishes a novel data-driven method to identify language network activation patterns in pediatric epilepsy through the use of the Principal Component Analysis (PCA) on functional magnetic resonance imaging (fMRI). A total of 122 subjects’ data sets from five different hospitals were included in the study through a web-based repository site designed here at FIU. Research was conducted to evaluate different classification and clustering techniques in identifying hidden activation patterns and their associations with meaningful clinical variables. The results were assessed through agreement analysis with the conventional methods of lateralization index (LI) and visual rating. What is unique in this approach is the new mechanism designed for projecting language network patterns in the PCA-based decisional space. Synthetic activation maps were randomly generated from real data sets to uniquely establish nonlinear decision functions (NDF) which are then used to classify any new fMRI activation map into typical or atypical. The best nonlinear classifier was obtained on a 4D space with a complexity (nonlinearity) degree of 7. Based on the significant association of language dominance and intensities with the top eigenvectors of the PCA decisional space, a new algorithm was deployed to delineate primary cluster members without intensity normalization. In this case, three distinct activations patterns (groups) were identified (averaged kappa with rating 0.65, with LI 0.76) and were characterized by the regions of: (1) the left inferior frontal Gyrus (IFG) and left superior temporal gyrus (STG), considered typical for the language task; (2) the IFG, left mesial frontal lobe, right cerebellum regions, representing a variant left dominant pattern by higher activation; and (3) the right homologues of the first pattern in Broca's and Wernicke's language areas. Interestingly, group 2 was found to reflect a different language compensation mechanism than reorganization. Its high intensity activation suggests a possible remote effect on the right hemisphere focus on traditionally left-lateralized functions. In retrospect, this data-driven method provides new insights into mechanisms for brain compensation/reorganization and neural plasticity in pediatric epilepsy.

VHITS: Vertical handoff initiation and target selection in a heterogeneous wireless network

Global connectivity, for anyone, at anyplace, at anytime, to provide high-speed, high-quality, and reliable communication channels for mobile devices, is now becoming a reality. The credit mainly goes to the recent technological advances in wireless communications comprised of a wide range of technologies, services, and applications to fulfill the particular needs of end-users in different deployment scenarios (Wi-Fi, WiMAX, and 3G/4G cellular systems). In such a heterogeneous wireless environment, one of the key ingredients to provide efficient ubiquitous computing with guaranteed quality and continuity of service is the design of intelligent handoff algorithms. Traditional single-metric handoff decision algorithms, such as Received Signal Strength (RSS) based, are not efficient and intelligent enough to minimize the number of unnecessary handoffs, decision delays, and call-dropping and/or blocking probabilities. This research presented a novel approach for the design and implementation of a multi-criteria vertical handoff algorithm for heterogeneous wireless networks. Several parallel Fuzzy Logic Controllers were utilized in combination with different types of ranking algorithms and metric weighting schemes to implement two major modules: the first module estimated the necessity of handoff, and the other module was developed to select the best network as the target of handoff. Simulations based on different traffic classes, utilizing various types of wireless networks were carried out by implementing a wireless test-bed inspired by the concept of Rudimentary Network Emulator (RUNE). Simulation results indicated that the proposed scheme provided better performance in terms of minimizing the unnecessary handoffs, call dropping, and call blocking and handoff blocking probabilities. When subjected to Conversational traffic and compared against the RSS-based reference algorithm, the proposed scheme, utilizing the FTOPSIS ranking algorithm, was able to reduce the average outage probability of MSs moving with high speeds by 17%, new call blocking probability by 22%, the handoff blocking probability by 16%, and the average handoff rate by 40%. The significant reduction in the resulted handoff rate provides MS with efficient power consumption, and more available battery life. These percentages indicated a higher probability of guaranteed session continuity and quality of the currently utilized service, resulting in higher user satisfaction levels.

Principal Component Analysis and Assessment of Language Network Activation Patterns in Pediatric Epilepsy

This dissertation establishes a novel data-driven method to identify language network activation patterns in pediatric epilepsy through the use of the Principal Component Analysis (PCA) on functional magnetic resonance imaging (fMRI). A total of 122 subjects’ data sets from five different hospitals were included in the study through a web-based repository site designed here at FIU. Research was conducted to evaluate different classification and clustering techniques in identifying hidden activation patterns and their associations with meaningful clinical variables. The results were assessed through agreement analysis with the conventional methods of lateralization index (LI) and visual rating. What is unique in this approach is the new mechanism designed for projecting language network patterns in the PCA-based decisional space. Synthetic activation maps were randomly generated from real data sets to uniquely establish nonlinear decision functions (NDF) which are then used to classify any new fMRI activation map into typical or atypical. The best nonlinear classifier was obtained on a 4D space with a complexity (nonlinearity) degree of 7. Based on the significant association of language dominance and intensities with the top eigenvectors of the PCA decisional space, a new algorithm was deployed to delineate primary cluster members without intensity normalization. In this case, three distinct activations patterns (groups) were identified (averaged kappa with rating 0.65, with LI 0.76) and were characterized by the regions of: 1) the left inferior frontal Gyrus (IFG) and left superior temporal gyrus (STG), considered typical for the language task; 2) the IFG, left mesial frontal lobe, right cerebellum regions, representing a variant left dominant pattern by higher activation; and 3) the right homologues of the first pattern in Broca's and Wernicke's language areas. Interestingly, group 2 was found to reflect a different language compensation mechanism than reorganization. Its high intensity activation suggests a possible remote effect on the right hemisphere focus on traditionally left-lateralized functions. In retrospect, this data-driven method provides new insights into mechanisms for brain compensation/reorganization and neural plasticity in pediatric epilepsy.

Solving the mystery of Guanxi-a sociological explanation of social exchange and social networking in Guanxi practice

Guanxi, loosely defined as "inter-personal relations" or "personal connections," is one of the key socio-cultural concepts in understanding Chinese society. This thesis presented a theoretical examination of the Chinese socio-cultural concept of guanxi. By using a broad survey of the available literature, this thesis established the following points: Social structures shape and define the development of guanxi practice in Chinese society. Guanxi relationships are based on the social exchange of gifts and favors in dyadic or multi-stranded social networks. While following the general rules of reciprocity found in social exchange, guanxi exchange is also governed by the internalized social norms such as mianzi (face) and renqing (humanized obligation underpinned by human sentiment). Guanxi relationships are also network-oriented, featuring ties based on familiarity and mutual trust, and characterized by an interplay between expressiveness and instrumentalism.

Algorithms for Geometric Matching, Clustering, and Covering

With the popularization of GPS-enabled devices such as mobile phones, location data are becoming available at an unprecedented scale. The locations may be collected from many different sources such as vehicles moving around a city, user check-ins in social networks, and geo-tagged micro-blogging photos or messages. Besides the longitude and latitude, each location record may also have a timestamp and additional information such as the name of the location. Time-ordered sequences of these locations form trajectories, which together contain useful high-level information about people's movement patterns.

The first part of this thesis focuses on a few geometric problems motivated by the matching and clustering of trajectories. We first give a new algorithm for computing a matching between a pair of curves under existing models such as dynamic time warping (DTW). The algorithm is more efficient than standard dynamic programming algorithms both theoretically and practically. We then propose a new matching model for trajectories that avoids the drawbacks of existing models. For trajectory clustering, we present an algorithm that computes clusters of subtrajectories, which correspond to common movement patterns. We also consider trajectories of check-ins, and propose a statistical generative model, which identifies check-in clusters as well as the transition patterns between the clusters.

The second part of the thesis considers the problem of covering shortest paths in a road network, motivated by an EV charging station placement problem. More specifically, a subset of vertices in the road network are selected to place charging stations so that every shortest path contains enough charging stations and can be traveled by an EV without draining the battery. We first introduce a general technique for the geometric set cover problem. This technique leads to near-linear-time approximation algorithms, which are the state-of-the-art algorithms for this problem in either running time or approximation ratio. We then use this technique to develop a near-linear-time algorithm for this

shortest-path cover problem.

Housing and Planning in London under the Conservative Government: Spatial impacts, social polarisation, sustainable development and social justice

This paper will be based on my continuing research on planning and housing development in London. It will focus on the proposals in the Government’s Housing and Planning Bill, which are likely to be enacted in Spring 2016. It will review the evidence of potential spatial impacts in terms of the supply of existing affordable homes and the location and affordability of new supply. This will be related to a review of the alternative development options for London’s growth in the context of the Mayor of London’s draft 2050 Infrastructure Plan. The paper will analyse the potential impact of new Government policy and legislation on whether London’s housing requirements can be delivered in accordance with the objectives of sustainable planning and social justice, and will also consider the constraints on the ability of the new Mayor of London, to be elected in May 2016 to achieve manifesto commitments.

Utilizing ICT to prevent loneliness and social isolation of the elderly. A literature review

Ageing of the population is a worldwide phenomenon. Numerous ICT-based solutions have been developed for elderly care but mainly connected to the physiological and nursing aspects in services for the elderly. Social work is a profession that should pay attention to the comprehensive wellbeing and social needs of the elderly. Many people experience loneliness and depression in their old age, either as a result of living alone or due to a lack of close family ties and reduced connections with their culture of origin, which results in an inability to participate actively in community activities (Singh & Misra, 2009). Participation in society would enhance the quality of life. With the development of information technology, the use of technology in social work practice has risen dramatically. The aim of this literature review is to map out the state of the art of knowledge about the usage of ICT in elderly care and to figure out research-based knowledge about the usability of ICT for the prevention of loneliness and social isolation of elderly people. The data for the current research comes from the core collection of the Web of Science and the data searching was performed using Boolean? The searching resulted in 216 published English articles. After going through the topics and abstracts, 34 articles were selected for the data analysis that is based on a multi approach framework. The analysis of the research approach is categorized according to some aspects of using ICT by older adults from the adoption of ICT to the impact of usage, and the social services for them. This literature review focused on the function of communication by excluding the applications that mainly relate to physical nursing. The results show that the so-called ‘digital divide’ still exists, but the older adults have the willingness to learn and utilise ICT in daily life, especially for communication. The data shows that the usage of ICT can prevent the loneliness and social isolation of older adults, and they are eager for technical support in using ICT. The results of data analysis on theoretical frames and concepts show that this research field applies different theoretical frames from various scientific fields, while a social work approach is lacking. However, a synergic frame of applied theories will be suggested from the perspective of social work.

Circular migration and the Internet: The role of social networks in the sociocultural context of Mexican residents in Barcelona

This work focuses on the study of the circular migration between America and Europe, particularly in the discussion about knowledge transfer and the way that social networks reconfigure the form of information distribution among people, that due to labor and academic issues have left their own country. The main purpose of this work is to study the impact of social media use in migration flows between Mexico and Spain, more specifically the use by Mexican migrants who have moved for  multiple years principally for educational purposes and then have returned to their respective locations in Mexico seeking to integrate themselves into the labor market. Our data collection concentrated exclusively on a group created on Facebook by Mexicans who mostly reside in Barcelona, Spain or wish to travel to the city for economic, educational or tourist reasons.  The results of this research show that while social networks are spaces for exchange and integration, there is a clear tendency by this group to "narrow lines" and to look back to their homeland, slowing the process of opening socially in their new context.

LDA-TM : A two-step approach to twitter topic data clustering

The Twitter System is the biggest social network in the world, and everyday millions of tweets are posted and talked about, expressing various views and opinions. A large variety of research activities have been conducted to study how the opinions can be clustered and analyzed, so that some tendencies can be uncovered. Due to the inherent weaknesses of the tweets - very short texts and very informal styles of writing - it is rather hard to make an investigation of tweet data analysis giving results with good performance and accuracy. In this paper, we intend to attack the problem from another aspect - using a two-layer structure to analyze the twitter data: LDA with topic map modelling. The experimental results demonstrate that this approach shows a progress in twitter data analysis. However, more experiments with this method are expected in order to ensure that the accurate analytic results can be maintained.

Participação Social e Redes Sociais Pessoais de Idosos

Objetivo: O objetivo central deste estudo é caracterizar as redes sociais pessoais de indivíduos com idade igual ou superior a 65 anos, a nível estrutural, funcional e relacional-contextual, analisando-as segundo o nível de participação social dos idosos ao longo da sua vida em estruturas comunitárias ligadas ao lazer, cultura, desporto, religião e voluntariado. Metodologia: Para a avaliação das variáveis em estudo foram utilizados o Instrumento de Análise da Rede Social Pessoal, versão para idosos (IARSP – Idosos) (Guadalupe, 2010; Guadalupe & Vicente, 2012) para avaliar as dimensões da rede social pessoal, um questionário para caracterizar as variáveis sociodemográficas e a participação social e a Satisfaction With Life Scale – SWLS (Diener, 1985) que permite avaliar o grau de satisfação com a vida. Participantes: A amostra é constituída por 567 idosos, com uma média de idades de 75 anos (DP=7,6), entre os 65 anos e os 98 anos, maioritariamente do sexo feminino (63,0%), casados ou em união de facto (53,7%) e com escolaridade (69,8%), sobretudo ao nível do quarto ano (51,3%). A maioria dos idosos inquiridos não vive só (79,4%) numa zona de residência maioritariamente inserida em aglomerado populacional em região rural (57,0%) e não usufrui de qualquer tipo de apoio de resposta social (75,5%). Resultados: A amostra divide-se entre os que participaram comunitariamente ao longo da vida (47,8%; n = 271) e os que não participaram (52,2%; n = 296), sendo que entre os que participam 16,7% fazem-no com elevada frequência. Os idosos do sexo feminino, com idade igual ou inferior a 75 anos, casados, com habilitações literárias e que vivem acompanhados, são os que têm uma maior probabilidade de ter uma participação social mais ativa. Os idosos que apresentam participação social têm uma rede maior, com um membro a mais em média (M = 8,52 vs. 7,51, p = 0,027), e uma composição distinta dos que não participam, com menor peso das relações familiares (M = 72,61% vs. 80,81%, p < 0,001), maior peso e mais relações de amizade (M = 15,43% vs. M = 9,24%, p < 0,001) e maior presença de relações de trabalho (M = 1,11% vs. 0,13%, p = 0,006). Relativamente às características funcionais, podemos constatar que a reciprocidade de apoio é percebida como maior (p = 0,010) entre os idosos que participam comunitariamente, não se verificando diferenças noutras variáveis funcionais e relacionais-contextuais. O nível de participação e a satisfação com o nível de participação correlacionam-se positivamente com a satisfação percebida com a vida (p < 0,001). Conclusão: As conclusões apontam para um efeito da participação social ao longo da vida em estruturas comunitárias nas características estruturais das redes sociais pessoais dos idosos, não se verificando interferência na maioria das características funcionais e nas relacionais-contextuais. Verificámos ainda que há uma associação entre a participação social e a satisfação com a vida, sendo mais satisfeitos os que participam em estruturas comunitárias. É possível constatar que a rede daqueles que referem ter participação social é tendencialmente maior e heterogénea na composição, quando comparada com as redes dos sem participação social, assumindo, assim, relevância na estruturação de uma rede mais diversa e ampla, devendo ser estimulada no sentido de promover uma rede com recursos potencialmente positivos e um envelhecimento mais ativo. / Objectives: The central objective of this study is to characterize the personal social networks of the elderly, aged 65 years or more, analyzing them according to the level of social participation throughout their life in community structures related to leisure, culture, sports, religion and volunteering. Methodology: For the evaluation of the variables we used the Social Network Analysis Tool (IARSP-elderly) (Guadalupe, 2010; Guadalupe Vicente, 2012) to assess the dimensions of the social network; a questionnaire to evaluate social participation; and the Satisfaction With Life Scale SWLS – (Diener, 1985) to acess the degree of satisfaction with life. Participants: The sample consists of 567 elderly, with an average age of 75 years old (SD = 7,595), between 65 and 98 years old, mostly female (63.0 %), married (53.7%) with education (69.8%), mainly with the 4th grade (51.3%). Most of the respondents do not live alone (79.4%) in agglomerations in rural region (57.0%) and are not users of social services (75.5%). Results: The sample is divided between those who had community participation throughout life (47.8 %; n = 271) and those who did not participated (52,2%; n = 296). Between the first, 16.7% do it with high frequency. The elderly women, aged less than 75 years old, married, with educational qualifications and living not alone, are those who have a higher likelihood of having a more active social participation. The elderly that present social participation have a larger network, with one more member (M = 8,52 vs. 7,51, p = 0,027), and a composition distinct from not participating, with less proportion of family relations (M = 72,61% vs. 80,81%, p < 0,001), greater proportion and more friendships (M = 15,43% vs. M = 9,24%, p < 0,001) and greater presence of working relations (M = 1,11% vs. 0,13%, p = 0,006). Regarding the functional dimension, the reciprocity of support is perceived as higher (p = 0.010) among seniors participating in community and there were no differences in other functional and relational-contextual variables. The level of participation and satisfaction with the level of participation correlate positively with perceived satisfaction with life (p <0.001). Conclusion: The findings point to an effect of lifelong social participation in community in structural characteristics of personal social networks of the elderly, not verifying interference in most of the functional and the contextual-relational characteristics. We have also found that there is an association between social participation and life satisfaction, being more satisfied when they participate in community structures. The social network of the elderly who reported having social participation tends to be larger and heterogeneous in composition compared with those without social participation, thus assuming importance in structuring a more diverse and extensive network, should be encouraged in order to promote a network with potentially positive resources and a more active aging.

Gaining by Giving? Peer Research into Service User and Carer Perceptions of Inclusivity in Higher Education

Service users and carers (SUAC) have made significant contributions to professional training in social work courses in Higher Education (HE) over the past decade in the UK. Such participation has been championed by government, academics and SUAC groups from a range of theoretical and political perspectives. Most research into the effectiveness of SUAC involvement at HE has come from the perspectives of academics and very little SUAC-led research exists. This qualitative peer research was led by two members of the University of Worcester’s SUAC group. Findings were that SUAC perceived their involvement brought benefits to students, staff, the University and the local community. Significant personal benefits such as finding a new support network, increased self-development and greater confidence to manage their own care were identified in ways that suggested that the benefits that can flow from SUAC involvement at HE are perhaps more far-reaching than previously recognised. Barriers to inclusion were less than previously reported in the literature and the humanising effects of SUAC involvement are presented as a partial antidote to an increasingly marketised HE culture.

Falls and the Social Isolation of Older Adults in the National Health and Aging Trends Study

Thesis (Ph.D.)--University of Washington, 2016-08