Internet Social Networks – Benefits and Risks

Доклад, поместен в сборника на Националната конференция "Образованието в информационното общество", Пловдив, май, 2012 г.

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.

The activity of the feminist online publications: challenges for the transmission of the feminist culture in Spain

Traditionally, big media corporations have contributed to hiding the women’s movement itself, as well as its main claims and topics of discussion (Marx, Myra y Hess, 1995; Rhode, 1995; Mendes, 2011). This has led the feminist movement to develop its own media generally print publications, usually, with a very specialized character and reduced audience. This is similar to what has occurred with quality main stream media, asthese publications have had to adapt themselves to a new communicatiion context, because of the financial crisis and  technological evolution. Feminist media has found in the Internet an excellent opportunity to access citizens and communicate their messages. , In view of this scene of change and renovation,  this article offers the results of a qualitative analysis focused on the experiences of four feminist online media sites edited in Spain: Pikaramagazine.com, Proyecto-kahlo.com, Mujeresenred.net and Laindependent.cat. Besides exploring the characteristics and content of these sites, the article pays attention to the virality of their contents spread through Facebook and Twitter. The onclusion estimates their social impact, insofar as they symbolize the specialization, diversification and dialogue promoted by the Web.

Recommending peers for learning: Matching on dissimilarity in interpretations to provoke breakdown

People recommenders are a widespread feature of social networking sites and educational social learning platforms alike. However, when these systems are used to extend learners’ Personal Learning Networks, they often fall short of providing recommendations of learning value to their users. This paper proposes a design of a people recommender based on content-based user profiles, and a matching method based on dissimilarity therein. It presents the results of an experiment conducted with curators of the content curation site Scoop.it!, where curators rated personalized recommendations for contacts. The study showed that matching dissimilarity of interpretations of shared interests is more successful in providing positive experiences of breakdown for the curator than is matching on similarity. The main conclusion of this paper is that people recommenders should aim to trigger constructive experiences of breakdown for their users, as the prospect and potential of such experiences encourage learners to connect to their recommended peers.

Integrating Scientific Publication into an Applied Gaming Ecosystem

Salman, M. et al. (2016). Integrating Scientific Publication into an Applied Gaming Ecosystem. GSTF Journal on Computing (JoC), Volume 5 (Issue 1), pp. 45-51.

Knowledge Workers and Associative Activity: An Examination of Knowledge Work Systems and Settings

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

Twitter e ciberativismo: o movimento social da hashtag #ForaMicarla em Natal-RN

The spatial and temporal fluidity conditioned by the technologies of social interaction online have been allowing that collective actions of protest and activism arise every day in cyberspace - the cyber-activism. If before these actions were located in geographical boundaries, today's demands and mobilizations extrapolate the location, connect to the global, and at the same time, return to the regional through digital virtuality. Within this context of the relationship between digital technology and global flow of sociability, emerges in October 2010 the social movement of the hashtag "#ForaMicarla", which means the dissatisfaction of cibernauts from Natal of Twitter with the current management of the municipality of Natal-RN, Micarla de Sousa (Green Party). We can find in the center of this movement and others who appeared in the world at the same time a technological condition of Twitter, with the hashtag "#". Given this scenario, this research seeks to analyze how the relationship of the agents of movement hashtag "ForaMicarla", based on the principle that it was formed in the Twitter network and is maintained on the platform on a daily basis, it can create a new kind of political culture. Thus, this study discusses theoretically the importance of Twitter and movements that emerge on the platform and through it to understand the social and political demands of the contemporary world and this public sphere, which now seems to include cyberspace

Motivations to interact with brands on Facebook – Towards a typology of consumer–brand interactions

In recent years, Facebook and other social media have become key players in branding activities. However, empirical research on consumer–brand interactions on Facebook is still in its infancy. Therefore, the aim of this research is to provide additional insights to brand managers on how to adapt their approaches to increase consumers’ interactions with brands on Facebook. In this study, we apply the uses and gratification theory proposed by Katz to develop a new typology of consumers based on consumer motivations to interact with brands on Facebook, and explore the type and intensity of these interactions. We identify five main motivations that might influence consumers’ interactions with a brand on Facebook: (i) social influence, (ii) search for information, (iii) entertainment, (iv) trust and (v) reward. Building on these five motivations, a classification using clustering techniques reveals four different groups of consumers: (i) ‘brand detached’, (ii) ‘brand profiteers’, (iii) ‘brand companions’ and (iv) ‘brand reliants’. Our results provide valuable and applicable insights for social media marketing activities, which will assist brand managers to develop strategies for effectively reaching and influencing the most desirable groups of consumers.

On-light: optical social network

Social networks are a recent phenomenon of communication, with a high prevalence of young users. This concept serves as a motto for a multidisciplinary project, which aims to create a simple communication network, using light as the transmission medium. Mixed team, composed by students from secondary and higher education schools, are partners on the development of an optical transceiver. A LED lamp array and a small photodiode are the optical transmitter and receiver, respectively. Using several transceivers aligned with each other, this con guration creates a ring communication network, enabling the exchange of messages between users. Through this project, some concepts addressed in physics classes from secondary schools (e.g. photoelectric phenomena and the properties of light) are experimentally veri ed and used to communicate, in a classroom or a laboratory.

Twitter e ciberativismo: o movimento social da hashtag #ForaMicarla em Natal-RN

The spatial and temporal fluidity conditioned by the technologies of social interaction online have been allowing that collective actions of protest and activism arise every day in cyberspace - the cyber-activism. If before these actions were located in geographical boundaries, today's demands and mobilizations extrapolate the location, connect to the global, and at the same time, return to the regional through digital virtuality. Within this context of the relationship between digital technology and global flow of sociability, emerges in October 2010 the social movement of the hashtag "#ForaMicarla", which means the dissatisfaction of cibernauts from Natal of Twitter with the current management of the municipality of Natal-RN, Micarla de Sousa (Green Party). We can find in the center of this movement and others who appeared in the world at the same time a technological condition of Twitter, with the hashtag "#". Given this scenario, this research seeks to analyze how the relationship of the agents of movement hashtag "ForaMicarla", based on the principle that it was formed in the Twitter network and is maintained on the platform on a daily basis, it can create a new kind of political culture. Thus, this study discusses theoretically the importance of Twitter and movements that emerge on the platform and through it to understand the social and political demands of the contemporary world and this public sphere, which now seems to include cyberspace

Perceções e atitude acerca da publicidade nas redes sociais e nos motores de pesquisa : uma análise comparativa

Mestrado em Marketing

Collaborative filtering and deep learning based recommendation system for cold start items

Recommender system is a specific type of intelligent systems, which exploits historical user ratings on items and/or auxiliary information to make recommendations on items to the users. It plays a critical role in a wide range of online shopping, e-commercial services and social networking applications. Collaborative filtering (CF) is the most popular approaches used for recommender systems, but it suffers from complete cold start (CCS) problem where no rating record are available and incomplete cold start (ICS) problem where only a small number of rating records are available for some new items or users in the system. In this paper, we propose two recommendation models to solve the CCS and ICS problems for new items, which are based on a framework of tightly coupled CF approach and deep learning neural network. A specific deep neural network SADE is used to extract the content features of the items. The state of the art CF model, timeSVD++, which models and utilizes temporal dynamics of user preferences and item features, is modified to take the content features into prediction of ratings for cold start items. Extensive experiments on a large Netflix rating dataset of movies are performed, which show that our proposed recommendation models largely outperform the baseline models for rating prediction of cold start items. The two proposed recommendation models are also evaluated and compared on ICS items, and a flexible scheme of model retraining and switching is proposed to deal with the transition of items from cold start to non-cold start status. The experiment results on Netflix movie recommendation show the tight coupling of CF approach and deep learning neural network is feasible and very effective for cold start item recommendation. The design is general and can be applied to many other recommender systems for online shopping and social networking applications. The solution of cold start item problem can largely improve user experience and trust of recommender systems, and effectively promote cold start items.

Collaborative filtering and deep learning based hybrid recommendation for cold start problem

Recommender systems (RS) are used by many social networking applications and online e-commercial services. Collaborative filtering (CF) is one of the most popular approaches used for RS. However traditional CF approach suffers from sparsity and cold start problems. In this paper, we propose a hybrid recommendation model to address the cold start problem, which explores the item content features learned from a deep learning neural network and applies them to the timeSVD++ CF model. Extensive experiments are run on a large Netflix rating dataset for movies. Experiment results show that the proposed hybrid recommendation model provides a good prediction for cold start items, and performs better than four existing recommendation models for rating of non-cold start items.

Travelers’ use of social media: A clustering approach

Research regarding the use of social media among travelers has mainly focused on its impact on travelers’ travel planning process and there is consensus that travel decisions are highly influenced by social media. Yet, little attention has been paid to the differences among travelers regarding their use of social media for travel purposes. Based on the use of travel social media, cluster analysis was employed to identify different segments among travelers. Furthermore, the study profiles the clusters based on demographic and other travel related characteristics. The findings of this study are important to online marketers to better understand traveler’s use of social media and their characteristics, in order to adapt online marketing strategies according to the profile of each segment.

Motivations to interact with brands on Facebook – Towards a typology of consumer–brand interactions

In recent years, Facebook and other social media have become key players in branding activities. However, empirical research on consumer–brand interactions on Facebook is still in its infancy. Therefore, the aim of this research is to provide additional insights to brand managers on how to adapt their approaches to increase consumers’ interactions with brands on Facebook. In this study, we apply the uses and gratification theory proposed by Katz (1959) to develop a new typology of consumers based on consumer motivations to interact with brands on Facebook, and explore the type and intensity of these interactions. We identify five main motivations that might influence consumers’ interactions with a brand on Facebook: (1) social influence, (2) search for information, (3) entertainment, (4) trust and (5) reward. Building on these five motivations, a classification using clustering techniques reveals four different groups of consumers: (1) “brand detached”, (2) “brand profiteers”, (3) “brand companions” and (4) “brand reliants”. Our results provide valuable and applicable insights for social media marketing activities, which will assist brand managers to develop strategies for effectively reaching and influencing the most desirable groups of consumers.