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Search engines may penalize sites they discover using black hat methods, either by reducing their rankings or eliminating their listings from their databases altogether. Such penalties can be applied either automatically by the search engines' algorithms, or by a manual site review. Infamous examples are the February 2006 Google removal of both BMW Germany and Ricoh Germany for use of deceptive practices and the April 2006 removal of the PPC Agency BigMouthMedia. All three companies, however, quickly apologized, fixed the offending pages, and were restored to Google's list. As a marketing strategy
Graduate students at Stanford University, Larry Page and Sergey Brin, developed "backrub," a search engine that relied on a mathematical algorithm to rate the prominence of web pages. The number calculated by the algorithm, PageRank, is a function of the quantity and strength of inbound links. PageRank estimates the likelihood that a given page will be reached by a web user who randomly surfs the web, and follows links from one page to another. In effect, this means that some links are stronger than others, as a higher PageRank page is more likely to be reached by the random surfer.
About Relations-public :ORM is a relatively new industry but has been brought to the forefront of professionals' consciousness due to the overwhelming and many times unpredictable nature of both professional journalistic content and amateur user-generated content (or UGC), the latter of which there is far more, and not the least because of the wide number websites that offer such an opportunity to visitors, typically with very low barriers to entry--often just by creating a screen name, registering one's birthday and a geographical location, and providing a valid email address to complete the account-creation process. Thus, the type of online content monitored in ORM spans professional, journalism sponsored by traditional news and media giants as well as user-created and user-generated blogs, ratings, reviews, and comments, and all manner of specialized websites about any particular subject, be it a person, group, company, business, product, event, concept, or trend.
ORM partly formed from a need to manage consumer generated media (CGM)
Relations-public SEO
Index Data Structures
Search engine architectures vary in the way indexing is performed and in methods of index storage to meet the various design factors. Types of indices include:
* Traditional or mainstream websites
* Social networks
* Consumer Review sites
* Sites which allow reviews of individuals.
* Collaborative Based Sites Such As Wikis
* Article Submission Directories
* Social news/bookmarking sites
* Collaborative Research sites such as Yahoo Answers, Rediff Q&A
* Independent discussion forums
* User-generated content (UGC)/Consumer Generated Media (CGM)
* Blogs
* Blogging communities )
* Improve customer satisfaction by gaining insights from consumers about what is good and bad about their product or services.
* Increase perceptions of brand by creating opportunities to listen to and engage consumers.
* Gain insights about competitors and their customers' perceptions about their products and services.
* Maintain shareholder value by mitigating risk by having ears close to the ground where opinions about a business are being formed and propagated.
* Engage in more effective public relations by understanding who the real influencers are.
* Gain understanding of the relationship between user generated content and traditional forms of online media, e.g. news, print, etc.
* Provide early warning systems for reactive and defensive PR.
* Reduce marketing spend by learning how to reach out to customers more cheaply.
* Reduce internal costs by employing services which save time and effort, as well as money.
* Help identify gaps for products and services which can be developed for profitable niche markets.
* Gain insight into online networks and keywords and key phrases found in user-generated content, which can help to bolster natural search results about the person, product, or business.
Relations-public Online :The examples above can be turned in more precise definitions using the concept of social evaluation defined above. At this point, we can propose to coin a new lexical item, image, whose character should be immediately evident from the following:
Image
Image is a global or averaged evaluation of a given target on the part of an agent. It consists of (a set of) social evaluations about the characteristics of the target. Image as an object of communication is what is exchanged in examples 1 and 2, above. In the second case, we call it third-party image. It may concern a subset of the target's characteristics, i.e., its willingness to comply with socially accepted norms and customs, or its skills. ways), nor its definition as pertaining to a precise agent. Indeed, we can define special cases of image, including third-party image, the evaluation that an agent believes a third party has of the target, or even shared image, that is, an evaluation shared by a group. Not even this last is reputation, since it tries to define in a too precisely the mental status of the group.
Relations-public Repair After parsing, the indexer adds the referenced document to the document list for the appropriate words. In a larger search engine, the process of finding each word in the inverted index (in order to report that it occurred within a document) may be too time consuming, and so this process is commonly split up into two parts, the development of a forward index and a process which sorts the contents of the forward index into the inverted index. The inverted index is so named because it is an inversion of the forward index.
The Forward Index
Relations-public Info Index Data Structures
Search engine architectures vary in the way indexing is performed and in methods of index storage to meet the various design factors. Types of indices include:
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