2 votes

Can we detect the emotions (or feelings) of a human through conversations with an AI?

I don't want to pour cold water over your approach, but I am very sceptical and (having worked in sentiment analysis myself) think it is way too simplistic. Various communicative intents are encoded ...
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  • 5,027
2 votes

Can we detect the emotions (or feelings) of a human through conversations with an AI?

I think you are definitely on a very sensible track. No one defines right or wrong in emotion field. It's not hard science. It's all theories. I have recently read a paper regarding emotions in ...
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  • 121
2 votes

Is there any research on the identification of a person's feelings using features such as facial expressions or body temperature?

Yes, there is research on this topic. The field that studies it is known as affective computing (AC). Emotion recognition seems to be a specific problem in affective computing, i.e. the recognition of ...
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  • 33k
2 votes
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How to keep track of the subject/entity in a sentence?

What you're describing is known as coreference resolution. More specifically, this example is anaphora resolution. The short answer is that this is an open research question and there is no well-...
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2 votes

What is the most accurate pretrained sentiment analysis model by 2019?

For best results, I'd recommend Google Cloud Machine Learning. It has [Natural Language Processing API] (https://cloud.google.com/natural-language/docs/basics) with Sentiment, Entity, and Entity-...
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1 vote

Is it ok to have an accuracy of 65% and a sensitivity of 90% with Naive Bayes for sentiment analysis?

I could get perfect sensitivity for positive sentiment if I always predict positive sentiment, but my accuracy could be 50%ish depending on the distribution of positive sentiment in the data. The ...
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1 vote
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How to train a sequence labeling model with annotations from three annotators?

Both ways are valid. It depends on what you want from the model and expect from the data. Generally though I would use 1 assumption and stick with it (unless there was a specific reason not to), so I ...
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  • 2,229
1 vote
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Sentiment analysis does not handle neturals

Yes, there is. You can try Spacy. Here you go. ...
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1 vote
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What is the difference between Sentiment Analysis and Emotion Recognition?

Sentiment in this context refers to evaluations, typically positive/negative/neutral. Sentiment Analysis can be applied to product reviews, to identify if the reviewer liked the product or not. This ...
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1 vote
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How can I find words in a string that are related to a given word, then associate a sentiment to that found word?

There are many ways to solve this problem. One way is to apply stemming or lemmatization to reduce your words. Using NLTK's Porter stemmer for example on healthy, healthier, healthiest, not healthy, ...
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1 vote

Why is an embedding of dimension 400 enough to represent 70000 words?

I finally grasped the concept of word embedding. Thanks to @nbro, after reading the 2 articles s/he recommended What Are Word Embeddings for Text? and Word embeddings the 1st article gives me a ...
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  • 181
1 vote
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Why is an embedding of dimension 400 enough to represent 70000 words?

The specific term you are looking for is "word embedding" and not just "embedding". How to numerically represent textual data? Neural networks (typically) require as inputs (and ...
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  • 33k
1 vote
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How do RNN's for sentiment classification deal with different sentence lengths?

One of the essential pre-processing we do on the corpus involves treating the variable-length sentences to a fixed length. There are various ways in which we can do this: Truncate This involves ...
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1 vote
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Recommended Modelling Technique for Influencer Marketing Scenario

It depends very much on the structure of the data. I would think about feature extraction first, which could be certain words occurring in the bio, and a class of user name ('real' name, numerical id,...
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1 vote

Can we detect the emotions (or feelings) of a human through conversations with an AI?

It could work using supervised learning , as long as you have the required dataset. However, a low error ratio using unsupervised learning of the human emotion spectrum would prove to be more ...
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