Name
Abstract | ||
|---|---|---|
AbstractPeople rely heavily on internet to fulfil even the minuscule of their need. According to a survey, 41% of time spent on web is for finding some information from search engines or reading some information. This is majorly due to easily accessible, cost effective and perceived high value information. But, this perceived high value information can prove fatal, if consumed without any authoritarian checks; especially if related to issues like health. Some template is necessitated to measure trustworthiness of such information. This paper explores a novel approach to quantify trust in such information-led websites. Analytical data is collected for various informational websites using similarweb.com and trust is modelled for these websites using human behaviour as an aggregate. Analytical data is believed to capture actual behaviour of each and every visitor visiting the website for information; thus making the study reliable and dependable. Results have been compared with some other acceptable studies and have found to be encouraging. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1504/ijaip.2019.099946 | Periodicals |
Field | DocType | Volume |
Internet privacy,Search engine,Computer science,Trustworthiness,Artificial intelligence,Visitor pattern,Machine learning,Health information,The Internet | Journal | 13 |
Issue | ISSN | Citations |
1-2 | 1755-0386 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Himani Bansal | 1 | 0 | 1.01 |
| Shruti Kohli | 2 | 6 | 3.82 |