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In general, you need labeled data to perform Sentiment Analysis. In case you don't have, you need to improvise. I found one article where the author claims that his implementation of unsupervised learning worked adequately. The post: Unsupervised Sentiment Analysis I quote some parts of it: The main idea behind this approach is that negative and positive ...


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The problem with Change point detection (or positive/negative trend detection), is that it depends on many things, including noise and sensitivity through time. For instance, you cannot send an alert when the scores just started being negative in one day. You have to wait a few days to see if the trend is actually bad or not. Consequently, you have to tune ...


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Here're my understandings: (1)[CLS] appears at the very beginning of each sentence, it has a fixed embedding and a fix positional embedding, thus this token contains no information itself. (2)However, the output of [CLS] is inferred by all other words in this sentence, so [CLS] contains all information in other words. This makes [CLS] a good representation ...


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