International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 163 - Number 11 |
Year of Publication: 2017 |
Authors: Akshay R, Arti Arya |
10.5120/ijca2017913761 |
Akshay R, Arti Arya . A Neoteric Data Preprocessing Technique for Online Surveys. International Journal of Computer Applications. 163, 11 ( Apr 2017), 9-12. DOI=10.5120/ijca2017913761
Online surveys is an essential research tool that are being applied in variety of research fields, including marketing, social and official statistics research and hence are one of the most popular data collection technique. Some people fill it genuinely and some do it randomly. Data collected through samples that are not filled genuinely may affect the analysis of the collected samples considerably. This paper proposes a preprocessing technique to select the samples that have genuine responses in order to make sure the final data collected from the survey is more precise and accurate. For this purpose the time duration an individual takes to provide his/her opinion to each question in questionnaire is captured. This captured time is used to check the percentage of questions that fall between the time ranges computed for each question using the proposed algorithm to indicate if the sample was filled genuinely. In doing so the samples that are found to be genuinely responded to, can be given more weight-age while analyzing the survey or randomly filled samples can be eliminated.