How to use (free..?) generative AI for summarizing content and extracting emotions/sentiments from answers to open-ended questions?
Hello, absolute beginner here… For research purposes,  I am facing the following problem.I have a medium-size dataset (2000 rows) of (one-line) answers to an open-ended question (“what will you take home and remember of…?” for a series of happy and sad events). It is in Italian.I wish to make a tool able to perform (at least part of) the following tasks:extract common patterns: widespread answers and emotionsgive examples of answers for specific patternscount statistics on these answers and emotionspoint out and highlight particular and atypical concernsImagine a question concerning the covid19 pandemic; an example of reply from the system might be:“A widespread feeling is loneliness, being separated from the beloved ones. There is a rediscovering of the time spent within family. 30% of answers are full of sorrow for the death of someone… One message reported the consciousness of how useless is life when you are alone…” and so on.I have tried different ways (chatgpt with some system of text splitting, gpt3 fby its api, some free approaches from python…) and different prompts.I am facing the problems of the limit in the number of tokens, and of short memory (I am sending the questionnaire answers in blocks, but the system forgets old ones and I am not succeeding in making it remember the context as I wish, and enrich it as  blocks are transmitted to it).Moreover, the answers generated by the systems are not really under my control: sometimes they gave me useful comments, sometimes they translated Italian into English (!), and so on.Of course a large part of the problem is my inexperience, but maybe I am not choosing the right way.So my question is: what is a good way to follow, possibly with free tools?ThanksGiorgio