Name
Abstract | ||
|---|---|---|
Search engines play a critical role in the diffusion of online information because they determine what content is easily visible to Web users. Major search engines, such as Google, Microsoft Live Search, and Yahoo!, provide two distinct types of results, organic and paid, each of which uses different mechanisms for selecting and ranking relevant Web pages. Using a third-party trust assurance program from BBB (Better Business Bureau) Online we find that vendors represented by websites in organic and paid results have varying reliability ratings. These ratings, based on overall customer experiences, may range from satisfactory to unsatisfactory. We empirically examine how vendors' reliability ratings from BBB Online are associated with cues (such as type of search result, relative price of a product, and number of sites selling the product) that can be observed or derived from organic and paid search results. Further, we apply a data mining technique to predict the vendors' BBB reliability ratings using those cues and achieve good performance. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.dss.2011.12.002 | Decision Support Systems |
Keywords | Field | DocType |
ranking relevant web page,web user,bbb reliability rating,major search engine,reliability rating,better business bureau,bbb online,visible cue,search engine,microsoft live search,search result,search engine marketing | Data mining,World Wide Web,Search engine,Web page,Ranking,Computer science,Search engine optimization,Relative price | Journal |
Volume | Issue | ISSN |
52 | 3 | 0167-9236 |
Citations | PageRank | References |
4 | 0.38 | 26 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhongming Ma | 1 | 133 | 7.33 |
| Olivia R. Liu Sheng | 2 | 18 | 2.71 |
| Gautam Pant | 3 | 593 | 31.72 |
| Alicia Iriberri | 4 | 130 | 7.42 |