Response quality

Response quality is a come up term for this project measuring that how many words the responses receive. The main idea behind it is to:

  1. quantify the text mining process

  2. explore responses receiving the poor or inadequate responses (i.e. getting fewer words).

Therefore, we research the response quality in this text by measuring the word count in each response. Here are some general questions to look for throughout this section of analysis:

  • What is the distribution of the word counts of response, question and description fields?

  • Is there any relationship between the word count of response, question and description fields and explanatory variables such as the question, sector name, canton name, partner name, etc.

We assume that the responses with a ‘larger word count’ have more quality than the responses with ‘smaller word count’. In other words, our assumption is based on that the more word a response has, the more developed and detailed it is.

Some forseen limitations are are based on the unequal distribution of the data. The word count of responses and questions can be related to other things, such as the questions require short answers. As a result, the responses tend to be shorter; therefore, those might be an obstacle for the analysis.

Additionally, we can have a cross-analysis to test these outcomes. It might be a good idea to have a small subset of data and ask an expert to test the assumptions qualitatively. For instance, we can take the first twenty responses with the highest word count and the last twenty responses with the lowest word count. It would be wise to chose the extreme directions because they point out the most considerable differences which make things easier when testing assumptions.

In the end, detecting the questions having high response quality would help choose which responses should be thoroughly analyzed in the text mining section, which is the next one.