Culture or social interaction? A study of influential factors on weblog design

The importance of blogs and social networking as medium of interactions had gain substantial popularity in mainstream media. Such popularity is due to blogs timely publication, ease of use and wide availability. Blogs hypertext and hyperlinks spread information and influence through an underlying social network. Taking into consideration that past studies on web design have focused on cultural traits on design elements, this paper aims to analyse the patterns on blog design from the perspectives of social influence and interactions. Examining design patterns from five networks of blogs using content analysis method, the results show that design of blogs in an online network shares similar elements and the pattern is different from one network to the other

Friend Suggestion and Friend Browsing in Web 2.0 Applications

Web 2.0 and social network applications have become increasingly popular. It is important for these applications to help users in maintaining their social networks by providing functions on friend suggestion and friend browsing. However, little study in this area has been reported in the literature. This paper proposes the design of two modules for friend suggestion and friend browsing. The first module is based on Hopfield Net spreading activation, while the second module is based on hyperbolic tree and self-organizing map. The proposed evaluation plan is also presented in the paper

Knowledge Seeking and Knowledge Sharing in a nonprofit organizational partner network: a social network analysis

This research empirically examines the online social network of a national, non-profit organization called the national alliance to reduce violence (NARV), non-profit organizations across the US which address the issue of interpersonal violence. As a network of practice, knowledge shared by the non-profit organizations originates across a breadth of experts in the disciplines of advocacy, science, practice and policy. Two problems served as the motivation for this research. First, how does the online network structure support current knowledge contribution and knowledge retrieval within the network? Second, how could the online network structure enhance knowledge contribution and knowledge retrieval to meet the needs of the organization? We acquired network structure and knowledge sharing data through the collection of survey responses from NARV’s membership list. The data were analyzed as a two-mode affiliation network using UCINET, For the first research question, we found that the action groups of research and public awareness are positioned to be strong sources of knowledge contribution within the current network due to the number of nodes with whom they are connected. For the second research question, we identified training and mentoring as the action group from which other nodes desire knowledge

How Do Bloggers Comment: An Empirical Analysis of the Commenting Network of a Blogging Community

The blog is one of the most familiar social media to Web users. Its social nature suggests that blogging is not only about writing and publishing bloggers’ experience and thoughts, but also about establishing social relationships and networks with others through various links including citations, blogrolls, comments, and trackbacks. We have a particular interest in comments, and develop a commenting model that considers both unidirectional and bidirectional commenting relationships. This paper presents a social network analysis of the commenting network of CSDN blogging community, the largest Chinese language IT blogging community in China. According to our findings, this is a sparse network, and the most noticeable nodes in it are a few central bloggers who possess a lot of incoming relationships. Each of them is surrounded by a number of ordinary bloggers who recognize the central blogger as their exclusive information source in a star topology. Our continuing study will focus on these central bloggers and examine their influences on the information diffusion in CSDN blogging community at the semantic level

An Enhanced Web Data Learning Method for Integrating Item, Tag and Value for Mining Web Contents

The Proposed System Analyses the scopes introduced by Web 2.0 and collaborative tagging systems, several challenges have to be addressed too, notably, the problem of information overload. Recommender systems are among the most successful approaches for increasing the level of relevant content over the 201C;noise.201D; Traditional recommender systems fail to address the requirements presented in collaborative tagging systems. This paper considers the problem of item recommendation in collaborative tagging systems. It is proposed to model data from collaborative tagging systems with three-mode tensors, in order to capture the three-way correlations between users, tags, and items. By applying multiway analysis, latent correlations are revealed, which help to improve the quality of recommendations. Moreover, a hybrid scheme is proposed that additionally considers content-based information that is extracted from items. We propose an advanced data mining method using SVD that combines both tag and value similarity, item and user preference. SVD automatically extracts data from query result pages by first identifying and segmenting the query result records in the query result pages and then aligning the segmented query result records into a table, in which the data values from the same attribute are put into the same column. Specifically, we propose new techniques to handle the case when the query result records based on user preferences, which may be due to the presence of auxiliary information, such as a comment, recommendation or advertisement, and for handling any nested-structure that may exist in the query result records

On violating one’s own privacy: N-adic utterances and inadvertent disclosures in online venues

Purpose: To understand the phenomena of people revealing regrettable information on the Internet, we examine who people think they’re addressing, and what they say, in the process of interacting with those not physically or temporally co-present. Design/methodology/approach: We conduct qualitative analyses of interviews with student bloggers and observations of five years’ worth of their blog posts, drawing on linguists’ concepts of indexical ground and deictics. Based on analyses of how bloggers reference their shared indexical ground and how they use deictics, we expose bloggers’ evolving awareness of their audiences, and the relationship between this awareness and their disclosures. Findings: Over time, writers and their regular audience, or “chorus,” reciprocally reveal personal information. However, since not all audience members reveal themselves in this venue, writers’ disclosures are available to those observers they are not aware of. Thus, their over-disclosure is tied to what we call the “n-adic” organization of online interaction. Specifically, and as can be seen in their linguistic cues, N-adic utterances are directed towards a non-unified audience whose invisibility makes the discloser unable to find out the exact number of participants or the time they enter or exit the interaction. Research implications: Attention to linguistic cues, such as deictics, is a compelling way to identify the shifting reference groups of ethnographic subjects interacting with physically or temporally distant others. Originality/value: We describe the social organization of interaction with undetectable others. N-adic interactions likely also happen in other on- and offline venues in which participants are obscured but can contribute anonymously.postprin

Finding the Key Players in Online Child Exploitation Networks

The growth of the Internet has been paralleled with a similar growth in online child exploitation. Since completely shutting down child exploitation websites is difficult (or arguably impossible), the goal must be to find the most efficient way of identifying the key targets and then to apprehend them. Traditionally, online investigations have been manual and centered on images. However, we argue that target prioritization needs to take more than just images into consideration, and that the investigating process needs to become more systematic. Drawing from a web crawler we specifically designed for extracting child exploitation website networks, this study 1) examines the structure of ten child exploitation networks and compares it to a control group of sports-related websites, and 2) provides a measure (network capital) that allows for identifying the most important targets for law enforcement purposes among our sample of websites. Results show that network capital — a combination between severity of content (images, videos, and text) and connectivity (links to other websites) — is a more reliable measure of target prioritization than more traditional measures of network centrality taken alone. Policy implications are discussed

Social network analysis of the video bloggers\u27 community in YouTube

This research studied the structure of the social network of the video blogger community on YouTube. It analyzed the social network structure of friends and subscribers of the 187 video bloggers on YouTube and calculated the social network measures. This thesis compares the results to the structure described by Warmbrodt et al. in 2007 and explains the reasons for the distinctions. The number of video bloggers has increased enormously, and the form of their interactions has changed. As a result, the video blogger social network has evolved from a core/periphery structure to one that is centralized. This indicates that the video blogger community on YouTube presently revolves around few central people in the network--Abstract, page iii

CiberSociedad y debate público en 140 caracteres : #paro y #corrupción

En esta investigación hemos pretendido estudiar si a través de Twitter, en un periodo temporal determinado, se ha generado debate relacionado con el paro y la corrupción y, de esta forma, analizar el potencial de Twitter como centro conversacional. La muestra analizada ha estado formada por los tweets recogidos desde el 08/02/2014 al 08/04/2014: 1.483 de #corrupción y 543 de #paro. Se confirma que la red social ha sido utilizada principalmente para compartir información, relativa a los hashtag #paro (543 tweets) y #corrupción (1.483 tweets) más que para interaccionar, desarrollándose un proceso de comunicación principalmente unidireccional y no bilateral. Una de las primeras ideas que surgen del análisis de contenido es la relación entre corrupción y paro y se concluye que el estudio de los tweets es una fuente valiosa para acercarnos a conocer la opinión pública en relación con temas de interés sociopolítico.In this research we have intended to study whether on Twitter, within a period of time, it has been generated some debate concerning unemployment and corruption and thus, analyze the potential of Twitter a conversational center. The sample analyzed was formed by tweets collected from 02/08/2014 to 04/08/2014: 1,483 of #corruption and 543 of #unemployment. It has been confirmed that the social network has been used mainly to share information about both hashtags #paro and # corruption rather than to interact among users, so it has been developed a mainly communication process unidirectional and not bilateral. One of the first ideas that come from the content analysis is the connection between corruption and unemployment. It might be concluded that the study of tweets is a valuable resource to know public opinion regarding socio-political issues