9/9 I love working with open responses because they can provide insights that established scales often don't. But not everyone has an army of research assistants or programming experience. We hope that SCORES will make the use of open-response data in research more accessible.
8/n Of course SCORES also has it's limitations. E.g. it doesn't work great for long responses. We include this guide to help researchers decide whether or not they want to use SCORES:
4/n SCORES has an intuitive, user-friendly interface (no programming knowledge required) and a tutorial mode that can guide researchers through the decision processes. You simply upload your data and select which columns you want to include in your analysis:
7/n It also shows different quality indices. It weighs them by default to select the ideal cluster number, but you can also use this view to make your own decision.
3/n SCORES clusters responses via word embeddings (which reflect similarity in meaning), similar to the process of reading through the responses, creating coding categories, and having human coders assign each response to a category.