BACKLINK ANALYSIS USING MOZRANK ALGORITHM OF BLOGS

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Applications (TIJCSA)

RESEARCH PAPER

Available Online at

http://www.journalofcomputerscience.com/

BACKLINK ANALYSIS USING

MOZRANK ALGORITHM OF BLOGS

S. Geetha

Research Scholar

Department Of Computer Science PSGR Krishnammal College for Women

Coimbatore, India [email protected]

K. Sathiyakumari Assistant Professor

Department Of Computer Application

GRGovindarajulu School of Applied Computer Technology Coimbatore, India

[email protected]

Abstract

Social networking has become very popular during the past few years, but it can still very difficult to understand for someone new to social networking. Social networking is based on a certain structure that allow people to both express their individuality and meet people with similar interests. This structure includes having profiles, friends, blog posts, widgets, and usually something unique to that particular social networking website such as the ability to ‘poke’ people on facebook or hi5. Blogs is another feature of some social networks is the ability to create own blog entries. While not as feature rich as blog hosts like wordpress or blogger, blogging through a social network is perfect for keeping people informed on own information. This paper represents a web page ranking algorithm using mozrank algorithm for blog searching and the ranking web sites. In this algorithm can be using online tool. The majesticseo and open site explorer using blog page ranking with the mozrank algorithm. Blog search engine uses the page rank algorithm to assign quantitatively authority values to blog web pages in a network.

Keyworks –

Page ranking, back link analysis, web mining, online social network, mozrank algorithm

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1. Introduction

1.1 Data Mining

Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Data mining tools can answer business questions that traditionally were too time consuming to resolve. They scour databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectations.

Data mining techniques can yield the benefits of automation on existing software and hardware platforms, and can be implemented on new systems, as existing platforms are upgraded and new products developed. When data mining tools are implemented on high performance parallel processing systems, they can analyze massive databases in minutes. Faster processing means that users can automatically experiment with more models to understand complex data. High speed makes it practical for users to analyze huge quantities of data. Larger databases, in turn, yield improved predictions.

1.2 Online Social Network

Online social network has disproportionate proscription and scheme for prospect out and encompass conceivable purpose. Like MySpace, Face book, LinkedIn, etc., MySpace is the most open, and user allowed search for and contact people beyond the intact network, whether they are devious members of the user social network or exhaustive strangers. Face book as a college social network application is much more proprietary and group oriented. Face book can only search for people that are in one of our substantiate networks. Those networks could embrace the company user work for, the college user attended, or even user high school. User can also join several of the thousands of smaller networks or groups that have been created by Face book users, some based on real-life organizations and some exist only in the minds of their founders.

1.3 Social Media

Social media analysis is the practice of gathering data from blogs and social media websites, such as Twitter, Face book, Digg and Delicious, and analyzing that data to inform business decisions. The most common use of social media analytics is gauging customer opinion to support marketing and customer service activities. There are number of types of tools foe various functions in the social media analytics process. These tools include application to identify the best social media sites to serve the purposes, applications to harvest data, a storage product or service, and data analytics software. However, text analysis and sentiment analysis technologies are the foundational components of social media analytics.

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© 2012, http://www.journalofcomputerscience.com - TIJCSA All Rights Reserved 32 Social media technologies take on many different forms including magazines, Internet forums, web logs, social blogs, microblogging, wikis, social networks, pod casts, photographs or pictures, video, rating and social book marking. By applying set of theories in the field of media research and social processes Kaplan and Heanlein created a classification scheme for different social media types in their business Horizons article published in 2010. According to Andreas Kalpan and Michael Heinlein there are six different types of social media: collaborative projects (e.g., Wikipedia), blogs and micro blogs (e.g., Twitter), content communities (e.g., You Tube), social networking sites (e.g., Face book), virtual game words (e.g., World of Watercraft), and virtual social words (e.g., Second Life). Technologies include: blogs, picture sharing, blogs, wall-postings, email, instant messaging, music-sharing, crowd sourcing and voice over IP, to name a few. Many of these social media services can be integrated via social network aggregation platforms. Social media network websites include sites like Face book, Twitter, Bebo and My space.

1.5 Realities of social media mining

The data mining of social media activity is now commonplace in business intelligence circles. Anything and everything on the internet is fair game extreme data mining practices. Once something is pushed out to the World Wide Web, it will forever be fodder for a business intelligence or data mining application somewhere in the cyberspace universe. Content created by a social network’s users to outside websites, advertisers, and affiliates for data mining an important component of the social networking business model, as data mining methodologies progress far beyond traditional demographic profiling into interpolation and statistical modeling based on swarms and cluster groups.

So powerful and lucrative is social media data mining that governments around the globe have begun to carefully scrutinize the need for regulation in this apace, especially with respect to protecting the privacy of their citizen’s that post data to these networks. While some regulation is probably needed, what concerns user is when the legislators of the free world start demanding social networks involuntarily hand over their user-generated content in order to better enable central governments to carry out their own “citizen intelligence” and data mining programs. That may be closer than any of user care to realize.

1.6 Text Mining and Web Mining

Text mining is the process of searching large volumes of documents from certain keywords or key phrases. By searching literally thousands of documents various relationships between the documents can be established. Using text mining however, we can easily derive certain patterns in the comments that may help identify a common set of customer perceptions not captured by the other survey questions. An extension of text mining is web mining. Web mining is an exciting new field that integrates data and text mining within a website. It enhances the web site with intelligent behavior, such as suggesting related links or recommending new products to the consumer. Web mining is especially exciting because it enables tasks that were previously difficult to implement. They can be configured to monitor and gather data from a

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© 2012, http://www.journalofcomputerscience.com - TIJCSA All Rights Reserved 33 wide variety of locations and can analyze the data across one or multiple sites. For example the search engines work on the principle of data mining.

1.7 Functions of Online Blogs

Blogs have become hugely popular as an entertainment portal, for news and for business purposes all at the same time. Blogs are gradually becoming very important in everyday news. In the past that blog posts have affected the political scenario of a country. Blogs gained popularity especially after 1998. Before blogs many forms of digital communication was popular including Usenet. But this was not popular with the masses as it was very expensive. Online blog became popular with open diary and later with Live journal. But blogger.com is chiefly responsible for its popularity in the post 1999 period. The website was largely renovated after it was purchased by Google in 2003, making it even more popular with the masses. Online blog can be of different types; these include text blogs, which is the most popular mode of blogging. Text blogs are basically articles or posts , which are posted by the author of the blog.. A blog page may include pictures, videos etc. There are blogging websites on the internet; these are also called blog-hosting websites. These sites provide the basic structure of a blog in which the user may make changes as per his wishes. Blogging can also take the shape of an online open diary. Many celebrities are into blogging in order to interact with their fans without much hustle.

A very important and essential part of a blog is the readers. Thus, the views of the readers are given due importance. For this reason blogs often contain places to put comments, suggestions, complaints etc. An online blog can also be used as an SEO or a search engine optimizer for a website. This is in order to popularize a website in search engines. The blog may contain links that takes the reader to the homepage of the original site. In this case it must be noted that the subject of the blog must be in accordance to the subject of the original website. More number of times the user is directed to the author's website, more traffic it gets. This makes it even more popular in the search engines. There are a few tips that can be followed in order to increase the popularity of the online blog and the original website at the same time. The articles of the blog must contain material pertaining to the subject of the website. The articles should also carry enough links in order to direct the reader to the website. Though the articles are for the purpose of increasing the popularity of the website; it shouldn't sound like an advertisement of the website.

1.8 Page Ranking Algorithm

Page Rank algorithm is the most commonly used algorithm for ranking the various pages. Working of the Page Rank algorithm depends upon link structure of the web pages. The Page Rank algorithm is based on the concepts that if a page contains important links towards it then the links of this page towards the other page are also to be considered as important pages. The Page Rank considers the back link in deciding the rank score. If the addition of the all the ranks of the back links is large then the page then it is provided a large rank.

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© 2012, http://www.journalofcomputerscience.com - TIJCSA All Rights Reserved 34 This paper represents a page-ranking algorithm for blog web pages using mozrank algorithm and it is using majesticseo online tool.

2.1 Tool Dataset

Open Site Explorer is powered by Mozscape, SEOmoz's index of the links on the internet. Beyond the standard link data, such as linking URLs, linking domains, and anchor text, Mozscape includes unique metrics that provide insight into the authority and trust of pages and domains. The major search engines, Google, Yahoo, and Bing, build similar indexes to help evaluate the importance and relevance of content on the web. Data comes from the World Wide Web itself. Indexing large amounts of data is allowing relevancy research and finds continued activities in competitive community driven for general purpose to web scale search engine.

News blog is used to educational, politic, social and marketing environments etc., It is referred to as students, research scholar and business persons. Because it is referred to one of the online social network. In this research work the data has been collected from (www.rte.in, www.independent.in, www.irishtimes.com, www.bbc.com/news, www.yahoo.com/news). These dataset is blog news sites. The RTÉ.ie is the website of Raidió Teilifís Éireann, Ireland's National Public Service Broadcaster in Ireland. The Independent.ie is using the news about UK News and World News. Wide range of international and local news, sports news, and commentary and opinion pieces. Independent Africa News - Bringing daily breaking stories from Africa. Independent online is the UK's trusted source of Africa news and in-depth reports.

The irishtimes.com is the online edition of The Irish Times and is the definitive brand of quality news aimed at Irish internet users and the Irish interest market. Since 1994 the Irish Times site has evolved from a series of simple text pages to an innovative multimedia platform that delivers up to the minute news as well as in-depth analysis of current affairs. The Irish Times site moved from ireland.com to irishtimes.com following the successful integration of the print and online newsrooms in early 2008. At the same time, the online subscription model, in place since 2002, was removed and replaced by a commercial model that is based on advertising. These initiatives were part of a significant development and investment programme in both print and online to broaden appeal to new audiences and to be more accessible to all readers. The BBC News for up-to-the-minute news, breaking news, video, audio and feature stories. BBC News provides trusted World and UK news as well as local news and finally yahoo is find latest India News, top news stories on India & around the World from Yahoo! News India.

Using online tool for this paper implementation, the Majestic SEO (Search Engine Optimization) surveys and maps the internet and has created the largest commercial link intelligence database in the world. Link data is also a component of search engine ranking, understanding the link profile of user own and competitor is constantly revisiting web pages and around a billion URLs a day. Higher end features include deeper analysis and API access, allowing developers to integrate Majestic Data with their own toolsets.

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© 2012, http://www.journalofcomputerscience.com - TIJCSA All Rights Reserved 35 MozRank represents a link popularity score. It reflects the importance of any given web page on the Internet. Pages earn MozRank by the number and quality of other pages that link to them. The higher the quality of the incoming links, the higher the MozRank. MozRank calculate this score on a logarithmic scale between 1 and 10. Thus, it's much easier to improve from a MozRank of 3 to 4 than it is to improve from 8 to 9. An "average" MozRank of what most people think of a normal page on the Internet is around 3.

2.3 Logarithmetic Scale

A logarithmic scale is a scale of measurement that displays the value of a physical quantity using intervals corresponding to orders of magnitude, rather than a standard linear scale. A logarithmic scale is used to graph exponential curves so that detail of small units can be shown in the same graph as the general curve shape at large unitshe data points have to be positive in order to take the log. The most common base for such logarithms is base-10.

The PageRank value for any page u can be expressed as:

i.e. the PageRank value for a page u is dependent on the PageRank values for each page v out of the set Bu (this set contains all pages linking to page u), divided by the number L(v) of links from page v.

The PageRank theory holds that even an imaginary surfer who is randomly clicking on links will eventually stop clicking. The probability, at any step, that the person will continue is a damping factor d. Various studies have tested different damping factors, but it is generally assumed that the damping factor will be set around 0.85. When calculating PageRank, pages with no outbound links are assumed to link out to all other pages in the collection. Their PageRank scores are therefore divided evenly among all other pages. In other words, to be fair with pages that are not sinks, these random transitions are added to all nodes in the Web, with a residual probability of usually d = 0.85, estimated from the frequency that an average surfer uses his or her browser’s bookmark feature.

So, the equation is as follows:

Where p1, p2,..., pN are the pages under consideration, M (pi) is the set of pages that link to pi, L(pj) is the number of outbound links on page pj , and N is the total number of pages.

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© 2012, http://www.journalofcomputerscience.com - TIJCSA All Rights Reserved 36 The PageRank values are the entries of the dominant eigenvector of the modified adjacency matrix. This makes PageRank a particularly elegant metric:

The eigenvector is

where ~π is the solution vector. Matrix representation of the Page Rank algorithm can be denote as:

where e is a column vector of all 1, M is the transition probability matrix which build from graph of links.

Adjacency function of the element Mi, j is 0 if page pi does not link to pj , and normalized such that, for each I

i.e. the elements of each column sum up to 1.

2.4 Algorithm of Page Rank

• Let u be a web page

• Let Fu be the set of forward links from u • Let Bu be the set of backlinks into u

• Let Nu=|Fu| be the number of forward links from u

• Let c be a normalization factor so that “the total rank of all web pages is constant” • Let E (u) be “some vector over the web pages that corresponds to a source of rank” Then, the Page Rank of page u is given by

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2.5.1 Technical Definition of MozRank (MR)

MozRank refers SEOmoz’s general, logarithmically scaled 10-point measure of global link authority (or popularity). MozRank is very similar in purpose to the measures of static importance (which means importance independent of a specific query) that are used by the search engines (e.g., Google's PageRank). Search engines often rank pages with higher global link authority ahead of pages with lower authority. Because measures like MozRank are global and static, this ranking power applies to a broad range of search queries, rather than pages optimized specifically for a particular keyword.The intuition behind MozRank is to leverage the democratic nature of the web. Every page has a vote and they can cast that vote by linking out to other web pages. Each time they link out all of the other links (votes) on the same page are slightly diluted. Thus, pages which link to many other pages aren’t able to overwhelm the votes from pages that only link to a few other pages. Otherwise, if one page linked to the same page 1000 times, it would unfairly make that page rank artificially high in. The takeaway is that a given web page has only a quantifiable amount of link juice (ranking power) to spread via links (votes). Pages that receive a lot of links (votes) are considered more authoritative and are able to more authoritatively endorse pages they link to.

2.5.2 Metrics of MozRank

Three levels of metrics can be used for MozRank: • MozRank,

• Domain level MozRank, • MozRank passed.

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Figure 2: Process of pages acquire PageRank

Figure 3: Ability of pages to pass PageRank

2.5.3 External Links

External Links are hyperlinks that point at (target) any domain other than the domain the link exists on (source). An external link is a link that points at an external domain.

• Top SEOs believe that external links are the most important source of ranking power. • External links pass Link Juice (ranking power) differently than internal links because the

search engines consider them as third-party votes.

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Many top SEOs believe that getting external links is the single most important objective for attaining high rankings. This stems from the idea that external links are one of the hardest metric to manipulate and thus one of the best ways for search engines to determine the popularity of a given web page. This idea was first used by the early search engine Alta Vista and later improved upon by Google.Google first made its mark by introducing the Stanford community to PageRank (an algorithm developed by Google co-founder Larry Page). This algorithm regarded hyperlinks as votes for popularity. The pages that had the most links pointing at them were considered the most popular. When they were deemed relevant for a particular query, the most popular and relevant pages would become the first pages listed in Google's results. Although this algorithm is much more complex today, it still likely includes the notion of external links as votes.Some of these metrics include:

• The trustworthiness of the linking domain. • The popularity of the linking page.

• The relevancy of the content between the source page and the target page. • The anchor text used in the link.

• The amount of links to the same page on the source page. • The amount of domains that link to the target page.

• The amount of variations that are used as anchor text to links to the target page. • The ownership relationship between the source and target domains.

In addition to these metrics, external links are important for two main reasons:

2.5.4 Popularity

Whereas traffic is a "messy" metric and difficult for search engines to measure accurately (according to Yahoo! search engineers), external links are both a more stable metric and an easier metric to measure. This is because traffic numbers are buried in private server logs while external links are publicly visible and easily stored. For this reason and others, external links are

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© 2012, http://www.journalofcomputerscience.com - TIJCSA All Rights Reserved 40 a great metric for determining the popularity of a given web page. This metric (which is roughly similar to toolbar PageRank) is combined with relevancy metrics to determine the best results for a given search query.

2.5.5 Relevancy

Links provide relevancy clues that are tremendously valuable for search engines. The anchor text used in links is usually written by humans (who can interpret web pages better than computers) and is usually highly reflective of the content of the page being linked to. Many times this will be a short phrase (e.g. "best aircraft article") or the URL of the target page (e.g. http://www.best-aircraft-articles.com). The target and source pages and domains cited in a link also provide valuable relevancy metrics for search engines. Links tend to point to related content. This helps search engines establish knowledge hubs on the Internet that they can then use to validate the importance of a given web document.

2.5.6

Internal Links

Internal Links are hyperlinks that point at (target) the same domain as the domain that the link exists on (source). Internal links are links that go from one page on a domain to a different page on the same domain. They are commonly used in main navigation.

These types of links are useful for three reasons: • They allow users to navigate a website.

• They help establish information hierarchy for the given website. • They help spread link juice (ranking power) around websites.

Internal Links are most useful for establishing site architecture and spreading link juice (URLs are also essential). For this reason, this section is about building an SEO friendly site architecture with internal links. On an individual page, search engines need to see content in order to list pages in their massive keyword-based indices. They also need to have access to a crawlable link structure - structures that let spiders browse the pathways of a website - in order to find all of the pages on a website. Hundreds of thousands of sites make the critical mistake of hiding or obfuscating their main link navigation in ways that search engines cannot access, thus impacting their ability to get pages listed in the search engines' indices.In the original PageRank formula, link weight is divided equally among the number of links on a page. This may not hold true today, but is still valuable to understanding the original intent. Next, a more complex example that shows PageRank flow back and forth between pages that link to one another:

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Finally, an example showing how PageRank can be "leaked". Rand and I both tend to believe has changed and refined the PageRank algorithm many times. However, familiarity and comfort with the original algorithm is certainly a responsibility for those who practice optimization of these blog results. As a caveat, I've included this graphic that Rand created several months ago for the blog to help show that while PageRank may present one way links as passing value, other concepts certainly exist.

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Figure 6: Anchor Text Distribution

3. Results

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Figure 8 – Sub domain Comparison for Five Websites

Figure 9 – Root domain Comparison for Five Websites

Finally here found that the links between the five-blog sites is very healthy and have more number of page authority rank. The rte.ie, independent.ie, irishtimes.com have the high rate back link values between them (90%). Among these five blog sites independent.ie found the high active internal and external links and also page.

4. Conclusion

Blog web page ranking method is used by hundreds of other lesser important searching utilities. One algorithm is in particular, that the Topic-Sensitive Page Rank. This will be the most effective and the one promising the most beneficial impact in the way users search for information in the Internet. Based on the algorithm used, the ranking algorithm provides a definite rank to resultant web pages. This way, when Search Engines crawl the Internet, they would index the blog web pages placing them in their corresponding Categories. Likewise, the Search Engines would need to modify the query request incorporating a field for the user to enter the Category or Sub-Category relevant to his query at that given time. This is efficient web page ranking algorithm with compatibility with global standards of web technology.

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