Name
Title | ||
|---|---|---|
Common attributes in an unusual context: predicting the desirability of a social match |
Abstract | ||
|---|---|---|
Social matching systems recommend people to other people. With the widespread adoption of smartphones, mobile social matching systems could potentially transform our social landscape. However, we have a limited understanding of what makes a good social match in the mobile context. We present a theoretical framework which outlines how a user's context and the rarity of different affinity measures in various contexts (match rarity) can be used to provide valuable social matches. We suggest that if a user attribute is very rare in a particular context, users will generally be more interested in an affinity match. We conducted a survey study to assess this framework with 117 respondents. We found that both context and match rarity significantly influence interest in a social match. These results validate the key aspects of the framework. We discuss the results in terms of implications for social matching system design. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1145/1864708.1864781 | RecSys |
Keywords | Field | DocType |
affinity match,social matching system design,unusual context,valuable social match,social match,common attribute,mobile context,social matching system,mobile social matching system,social landscape,good social match,particular context,system design | Data mining,Mobile context,Computer science,Systems design,Knowledge management,Survey research,Social matching | Conference |
Citations | PageRank | References |
6 | 0.50 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Julia M. Mayer | 1 | 58 | 4.98 |
| Sara Motahari | 2 | 40 | 4.46 |
| Richard P. Schuler | 3 | 28 | 2.76 |
| Quentin Jones | 4 | 438 | 38.48 |