Epicollect5 mainly used as a data collection tool. However it can be also used in other innovative ways also. In social media related research, specifically YouTube related research, it cab be used to identify or segregate unique video though URL link of the videos. This will reduce lots of time and efforts of the investigators, as there will be no need of duplicate video removal during later stage of the study. Is there any published article globally, which one has already proof this hypothesis?
Can you please provide an example of how you would use Epicollect5 to achieve that?
There are many scientific published research articles on YouTube related information. But in all the research articles, 4-5 authors watched the videos independently, and entered the data in excel sheet. And in the later on of the study, authors had to spend lots of time in duplicate video removal. But this can be completely avoided by entering data in epicollect5 from the starting. Four-five authors can easily watched the videos independently, due uniqueness check in the URL field of the videos, duplicate video will not be accepted. This will save lots of time on unnecessary duplicate videos screening.
This is the completely new way of using epicollect5 apart from its role in data collection.
If you are looking for a uniqueness constraint on the entries collected have a look at →