Experiments on Data Preprocessing of Persian Blog Networks

Abstract — Social networks analysis and exploring is important for researchers, sociologists, academics, and various businesses due to their information potential. Because of the large volume, diversity, and the data growth rate in web 2.0, some challenges have been made in these data analysis. Based on definitions, weblogs are a form of social networking. So far, the majority of studies and researches in the field of weblog networks analysis and exploring their stored data have been based on international data sets. In this paper, a framework for preprocessing and data analysis in weblog networks is presented and the results of applying it on a Persian weblog network, as a case study, are expressed. Keywords- Preprocessing, Weblog, Social Networks Analysis, Data Set. I. I NTRODUCTION Social networks have provided a new form of social relationships in cyberspace by using information technology which is expanding with a considerable speed around the world. In 1960, for the first time, a topic as social network was introduced in Illinois University in United States. After that, in 1997, the first social network site launched to address “SixDegrees.com” [16]. According to statistics, number of social networks in the world has become more than a few hundred millions which Facebook with 1.4 billion members is the largest and the most popular social network among them. LinkedIn, Twitter, and Google+ are in the next levels and 58% of internet users are member of at least one social network [17]. The first national social network in Iran was launched in almost ten years ago named “Cloob”. There is not any formal statistics about Persian social networks growth, members, features, and activities; however, in 2009, while among the top 20 worldwide popular sites, 8 sites were social networks; in Iran this statistics was 13 social networks sites among the top 20 popular sites, which some of these 13 sites were Persian weblog providers [6]. In all the web mining, data mining, text mining, and social networks analysis studies and researches, data preprocessing is one of the main stages and an integral part of exploring process; however in the most of researches, due to difficulty in obtaining and collecting large volume data, preprocessing stage is done on preprocessed or low volume data to accelerate this step. According to structure, weblogs are also a manifestation of social networks. Persian weblog networks analysis has been mainly focused on “PersianBlog”. These researches have been based on datasets prepared by other researchers and structural data obtained from web crawlers. Also, a low volume data has been processed because of processing limitations [1][10][11]. In another study [3], data stored in a Persian language social network named “ParsiYar” has been studied. This dataset contains information about users’ profile, their friendships, and their membership in social groups which its preprocessing results are in [3]. Based on social network analysis definition, weblogs service providers are a form of social network because of their structure. In the simple form, each weblog is node and links between them are considered as edges. Due to special characteristics of Persian language (such as encoding, font, etc.), Persian weblog creation requires special facilities; this is why number of Persian weblogs was low before Persian language specific hosts adventure. Fortunately, at present, there is considerable number of hosts for Persian weblogs, such as Blogfa, ParsiBlog, MihanBlog, and PersianBlog [11]. Persian language people have a great tendency to weblog creation; so that, according to statistics, at present, Iran by 700 thousands blogs is the ninth country based on number of blogs. However, not all of these weblogs are active and number of every few days updated of them is 400 thousands [15]. This paper proposes a framework for weblog networks data preprocessing to social networks exploring and analyzing. The rest of paper is as follow: in section 2, weblogs environment as a social network are studied and some definitions are presented. Section 3, presents proposed framework and section 4, demonstrates the result of applying