Questions tagged [sentiment-analysis]

For questions about sentiment analysis in AI.

Opinion mining (sometimes known as sentiment analysis or emotion AI) refers to the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine.

Generally speaking, sentiment analysis aims to determine the attitude of a speaker, writer, or other subject with respect to some topic or the overall contextual polarity or emotional reaction to a document, interaction, or event. The attitude may be a judgment or evaluation (see appraisal theory), affective state (that is to say, the emotional state of the author or speaker), or the intended emotional communication (that is to say, the emotional effect intended by the author or interlocutor).
Sentiment Analysis (wiki)

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

Can we detect the emotions (or feelings) of a human through conversations with an AI? Something like a "confessional", disregarding human possibilities to lie. Below, I have the categories joyful, sadness, anger, fear and affection. For each…
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What is the difference between Sentiment Analysis and Emotion Recognition?

I found Sentiment Analysis and Emotion Recognition as two different categories on paperswithcode.com. Should both be the same as my understanding? If not what's the difference?
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Is there any research on the identification of a person's feelings using features such as facial expressions or body temperature?

People could be sad, happy, depressive, angry, nervous, calm, relaxed, bored, etc. I don't know how to express all of these feelings and emotions in English terms (I'm not an English native speaker), which would enable me to search for research…
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VIsual/musical/multimedia discourse (analysis) - are there such notions?

Formal semantics of natural language perceives sentences as logical expressions. Full paragraphs and even stories of natural language texts are researched and formalized using discourse analysis (Discourse Representation Theory is one example). My…
TomR
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Integration of Sentiment analysis in CRM

What is the process for integrating sentiment analysis in a CRM? What I am searching for is a system which analyzes the customer comments or reviews using the CRM and finds out the customer sentiment on the services provided by the system or company…
SRJ577
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Recommended Modelling Technique for Influencer Marketing Scenario

I have an approximately 90,000 row dataset that has information of social media profiles which has columns for biography, follower count, language spoken, name, username and the label (to identify whether the profile is that of an influencer, brand…
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How can I apply naive Bayes classifier for three classes (Positive, Negative and Neutral) in text data?

I found a naive Bayes classifier for positive sentiment or a negative sentiment Citius: A Naive-Bayes Strategy for Sentiment Analysis on English Tweets. But with most available datasets online, sentiments are classified into 3 types: positive,…
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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?

I came up with an NLP-related problem where I have a list of words and a string. My goal is to find any word in the list of words that is related to the given string. Here is an example. Suppose a word from the list is healthy. If the string has any…
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Bert for Sentiment Analysis - Connecting final output back to the input

I have not found a lot of information on this, but I am wondering if there is a standard way to apply the outputs of a Bert model being used for sentiment analysis, and connect them back to the initial tokenized string of words, to gain an…
JSS
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How do RNN's for sentiment classification deal with different sentence lengths?

I have been doing a course which teaches you about Deep Neural Networks, during one of the exercises I was made to make an RNN for sentiment classification which I did, but I did not understand how an RNN is able to deal with sentences of different…
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What would be the steps to create an sentiment analysis chatbot?

We have been assigned a project, in which we have to create a chatbot which will ask question, take the replies, analyse them and give an approximate assessment of the current emotional state of the person. There are two aspects of the project,…
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Is there something like person-specific sentiment analysis?

Sentiment analysis, as we know, measures "Cake sucks" as say -0.4, and "Cake is great" as 0.7. What I'm looking for is something a bit different like so: Given input text data written by 1 person (say a blog) Predict how they (the person who wrote…
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Can Facebook's LASER be used like BERT?

Can Facebook's LASER be fine-tuned like BERT for Question Answering tasks or Sentiment Analysis? From my understanding, they created an embedding that allows for similar words in different languages to be close to each other. I just don't understand…
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Given the word embeddings, how do I create the sentence composed of the corresponding words?

I have done some reading. I want to implement an LSTM with pre-trained word embeddings (I also have plans to create my word embeddings, but let's cross that bridge when we come to it). In any given sentence, you don't usually need to have all the…
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How to keep track of the subject/entity in a sentence?

I'm working on Sentiment Analysis, using HuggingFace to perform sentiment analysis on articles classifier = pipeline('sentiment-analysis', model="nlptown/bert-base-multilingual-uncased-sentiment") classifier(['We are very happy to show you the …
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