IDENTIFYING INFLUENTIAL BLOGGERS

This project addresses the problem of identifying influential bloggers in a web blog community. It investigates the problem of identifying influential bloggers by scoring each blog post, posted by bloggers, based on influential factors and ranking bloggers accordingly. There exists preliminary models that attempted to solve the problem but they lack some of important aspects of the blogosphere. In this project we try to combine and improve the methodologies and ideas present in the previous models. We have introduced a new influence factor, which is a combination of facebook likes and shares, into the literature that can further evaluate blog posts efficiently. To capture the true influence we have mined each comment on a blog post to know the tone (agree or disagree) of the commenter, and evaluated the post accordingly. We also utilized the novelty parameter in our approach which represents the quality or goodness of the blog post. The experiment results proved that our approach is able to capture the true influence of each blog post and rank bloggers efficiently

IDENTIFYING INFLUENTIAL BLOGGERS ON THE WEB

Blog has take an important aspect of internet since the introduction of Web 2.0 technology because blog as been away to influence others who read the blogs. People now have interest in finding materials and friends on the internet.Many users visit blog sites to read the posts and comment on them. Most people do read blog to gather informationon things that are important before take major decision about them. Because blogger always share their experienceon a topic for others to comments and through this others share their own experience. With the impact thatinfluential blogger have in a community. The benefits of achieving competitive advantages in a blog community byidentify influential blogger have created several research gaps and the popularity of these services has make theproblem of identifying the most influential bloggers significant, since its solution can lead to major benefits for theusers of this services i.e. education, politic, participatory journalism, advertising, searching, commerce etc. Thecurrent works in this regard ignore some important aspects of the blogsphere. This paper focuses on using acrossbreed method as an improvement to the existing methodologies. With the introduction of new parametersFBCount and Mining Comments the new approach show that the score of each blog post reflect quality andgoodness of blog post. A program prototype was designed to calculate the influential bloggers. The results obtainedconfirm that current approach could significantly identify influential of bloggers on the web and the proposed modelhas better performance than other approaches. There are still a few of avenues for the future research. Future workcan include full implementation of the program prototype and try to improve on it to directly get the parameters usedfrom the blog post on the web in a blog community, more parameters like twitter shares, G+1s Pin shares etc can beincluded into the literature and check for the behavior of the influence and future research can investigate more timein deciding weight parameter that is crucial for tuning between different influential factors.Keyword: Blog, Blogger, Social networks, Blogosphere, Influential bloggers, Influential, Models

Identifying Influential Bloggers: Time Does Matter

Blogs have recently become one of the most favored services on the Web. Many users maintain a blog and write posts to express their opinion, experience and knowledge about a product, an event and every subject of general or specific interest. More users visit blogs to read these posts and comment them. This "participatory journalism" of blogs has such an impact upon the masses that Keller and Berry argued that through blogging "one American in tens tells the other nine how to vote, where to eat and what to buy" \cite{keller1}. Therefore, a significant issue is how to identify such influential bloggers. This problem is very new and the relevant literature lacks sophisticated solutions, but most importantly these solutions have not taken into account temporal aspects for identifying influential bloggers, even though the time is the most critical aspect of the Blogosphere. This article investigates the issue of identifying influential bloggers by proposing two easily computed blogger ranking methods, which incorporate temporal aspects of the blogging activity. Each method is based on a specific metric to score the blogger's posts. The first metric, termed MEIBI, takes into consideration the number of the blog post's inlinks and its comments, along with the publication date of the post. The second metric, MEIBIX, is used to score a blog post according to the number and age of the blog post's inlinks and its comments. These methods are evaluated against the state-of-the-art influential blogger identification method utilizing data collected from a real-world community blog site. The obtained results attest that the new methods are able to better identify significant temporal patterns in the blogging behaviour

Models of Social Groups in Blogosphere Based on Information about Comment Addressees and Sentiments

This work concerns the analysis of number, sizes and other characteristics of groups identified in the blogosphere using a set of models identifying social relations. These models differ regarding identification of social relations, influenced by methods of classifying the addressee of the comments (they are either the post author or the author of a comment on which this comment is directly addressing) and by a sentiment calculated for comments considering the statistics of words present and connotation. The state of a selected blog portal was analyzed in sequential, partly overlapping time intervals. Groups in each interval were identified using a version of the CPM algorithm, on the basis of them, stable groups, existing for at least a minimal assumed duration of time, were identified.Comment: Gliwa B., Ko\'zlak J., Zygmunt A., Models of Social Groups in Blogosphere Based on Information about Comment Addressees and Sentiments, in the K. Aberer et al. (Eds.): SocInfo 2012, LNCS 7710, pp. 475-488, Best Paper Awar

Analysis of roles and groups in blogosphere

In the paper different roles of users in social media, taking into consideration their strength of influence and different degrees of cooperativeness, are introduced. Such identified roles are used for the analysis of characteristics of groups of strongly connected entities. The different classes of groups, considering the distribution of roles of users belonging to them, are presented and discussed.Comment: 8th International Conference on Computer Recognition Systems, CORES 201

New Media, New Influencers and Implications for Public Relations

Marketers and public relations professionals today are confronted with an astounding array of new communications channels. Internet-based social media tools like blogs, podcasts, online video and social networks are giving voice to the opinions of millions of consumers. While mainstream media continues to play a vital role in the dissemination of information, even these traditional channels are increasingly being influenced by online conversations. The "new influencers" are beginning to tear at the fabric of marketing as it has existed for 100 years, giving rise to a new style of marketing that is characterized by conversation and community. Marketers are responding to these forces with a mixture of excitement, fear and fascination. They're alarmed at the prospect of ceding control of their messages to a community of unknowns. Yet at the same time they're excited about the prospect of leveraging theese same tools to speak directly to their constituents without the involvement of media intermediaries.The Society for New Communications Research set out to conduct an examination of how influence patterns are changing and how communications professionals are addressing those changes by adopting social media. The goals were to discover how organizations:Define new influencers;Communicate and create relationships with them;Use social media to create influence; andMeasure the effects of these efforts.Another goal of the study was to use these discoveries to offer a set of recommendations to professional communicators

Mining online diaries for blogger identification

In this paper, we present an investigation of authorship identification on personal blogs or diaries, which are different from other types of text such as essays, emails, or articles based on the text properties. The investigation utilizes couple of intuitive feature sets and studies various parameters that affect the identification performance. Many studies manipulated the problem of authorship identification in manually collected corpora, but only few utilized real data from existing blogs. The complexity of the language model in personal blogs is motivating to identify the correspondent author. The main contribution of this work is at least three folds. Firstly, we utilize the LIWC and MRC feature sets together, which have been developed with Psychology background, for the first time for authorship identification on personal blogs. Secondly, we analyze the effect of various parameters, and feature sets, on the identification performance. This includes the number of authors in the data corpus, the post size or the word count, and the number of posts for each author. Finally, we study applying authorship identification over a limited set of users that have a common personality attributes. This analysis is motivated by the lack of standard or solid recommendations in literature for such task, especially in the domain of personal blogs. The results and evaluation show that the utilized features are compact while their performance is highly comparable with other larger feature sets. The analysis also confirmed the most effective parameters, their ranges in the data corpus, and the usefulness of the common users classifier in improving the performance, for the author identification task