Web Mining for Social Network Analysis:A Review, Direction and Future Vision.
Clicks: 274
ID: 13849
2016
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Popular Article
72.0
/100
274 views
223 readers
Trending
AI Quality Assessment
Not analyzed
Readership in this journal
PopularRanked #31 of 148 articles by views in adbu journal of engineering technology
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 148 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Although web is rich in data, gathering this data and making sense of this data is extremely difficult due to its unorganised nature. Therefore existing Data Mining techniques can be applied toextract information from the web data. The knowledge thus extracted can also be used for Analysis of Social Networks and Online Communities. This paper gives a brief insight to Web Mining and Link Analysis used in Social Network Analysis and reveals the algorithms such as HITS, PAGERANK, SALSA, PHITS, CLEVER and INDEGREE which gives a measure to identify Online Communities over Social Networks. The most common amongst these algorithms are PageRank and HITS. PageRank measures the importance of a page efficiently with the help of inlinks in less time, while HITS uses both inlinks and outlinks to measure the importance of a web page and is sensitive to user query. Further various extensions to these algorithms also exist to refine the query based search results. It opens many doors for future researches to find undiscovered knowledge of existing online communities over various social networks. Keywords:Web Structure Mining, Link Analysis, Link Mining, Online Community Mining
| Reference Key |
singh2016webadbu
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Verma Gulhati Manjula, Yumnam Jayanta Singh; |
| Journal | adbu journal of engineering technology |
| Year | 2016 |
| DOI |
DOI not found
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.