Ipoll: Automatic polling using online search
© Springer International Publishing Switzerland 2014. For years, opinion polls rely on data collected through telephone or person-to-person surveys. The process is costly, inconvenient, and slow. Recently online search data has emerged as potential proxies for the survey data. However considerable h...
| Main Authors: | , , , , |
|---|---|
| Format: | Journal Article |
| Published: |
Springer Verlag
2014
|
| Online Access: | http://hdl.handle.net/20.500.11937/45036 |
| _version_ | 1848757170385977344 |
|---|---|
| author | Nguyen, T. Phung, D. Luo, W. Tran, The Truyen Venkatesh, S. |
| author_facet | Nguyen, T. Phung, D. Luo, W. Tran, The Truyen Venkatesh, S. |
| author_sort | Nguyen, T. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © Springer International Publishing Switzerland 2014. For years, opinion polls rely on data collected through telephone or person-to-person surveys. The process is costly, inconvenient, and slow. Recently online search data has emerged as potential proxies for the survey data. However considerable human involvement is still needed for the selection of search indices, a task that requires knowledge of both the target issue and how search terms are used by the online community. The robustness of such manually selected search indices can be questionable. In this paper, we propose an automatic polling system through a novel application of machine learning. In this system, the needs for examining, comparing, and selecting search indices have been eliminated through automatic generation of candidate search indices and intelligent combination of the indices. The results include a publicly accessible web application that provides real-time, robust, and accurate measurements of public opinions on several subjects of general interest. |
| first_indexed | 2025-11-14T09:23:50Z |
| format | Journal Article |
| id | curtin-20.500.11937-45036 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:23:50Z |
| publishDate | 2014 |
| publisher | Springer Verlag |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-450362017-01-30T15:17:54Z Ipoll: Automatic polling using online search Nguyen, T. Phung, D. Luo, W. Tran, The Truyen Venkatesh, S. © Springer International Publishing Switzerland 2014. For years, opinion polls rely on data collected through telephone or person-to-person surveys. The process is costly, inconvenient, and slow. Recently online search data has emerged as potential proxies for the survey data. However considerable human involvement is still needed for the selection of search indices, a task that requires knowledge of both the target issue and how search terms are used by the online community. The robustness of such manually selected search indices can be questionable. In this paper, we propose an automatic polling system through a novel application of machine learning. In this system, the needs for examining, comparing, and selecting search indices have been eliminated through automatic generation of candidate search indices and intelligent combination of the indices. The results include a publicly accessible web application that provides real-time, robust, and accurate measurements of public opinions on several subjects of general interest. 2014 Journal Article http://hdl.handle.net/20.500.11937/45036 Springer Verlag restricted |
| spellingShingle | Nguyen, T. Phung, D. Luo, W. Tran, The Truyen Venkatesh, S. Ipoll: Automatic polling using online search |
| title | Ipoll: Automatic polling using online search |
| title_full | Ipoll: Automatic polling using online search |
| title_fullStr | Ipoll: Automatic polling using online search |
| title_full_unstemmed | Ipoll: Automatic polling using online search |
| title_short | Ipoll: Automatic polling using online search |
| title_sort | ipoll: automatic polling using online search |
| url | http://hdl.handle.net/20.500.11937/45036 |