Quest_SA: Preprocessing Method for Closed-Ended Questionnaires Using Sentiment Analysis through Polarity

<table class="table-group" id="tab11"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td class="align_left">No. of responses</td><td class="align_center">MAE</td><td class="align_center">Accuracy</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td class="align_left">200</td><td class="align_center">5</td><td class="align_center">97.5</td></tr><tr><td class="align_left">400</td><td class="align_center">15</td><td class="align_center">96.25</td></tr><tr><td class="align_left">600</td><td class="align_center">20</td><td class="align_center">96.67</td></tr><tr><td class="align_left">800</td><td class="align_center">25</td><td class="align_center">96.91</td></tr><tr><td class="align_left">1,000</td><td class="align_center">25</td><td class="align_center">97.5</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>MAE and accuracy for general self-efficacy.</div>

Mobile Information Systems

tab11

Table 11

Table 11: Quest_SA: Preprocessing Method for Closed-Ended Questionnaires Using Sentiment Analysis through Polarity 