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What is Sentiment Analysis
1.
Also known as emotion AI or opinion mining is the systematic identification, quantification, extraction, and study of emotional states and subjective information using natural language processing (NLP), biometrics, text
analysis
, and computational linguistics.
Learn more in: Analyzing and Predicting Learner Sentiment Toward Specialty Schools Using Machine Learning Techniques
2.
An application for systematically identifying, extracting, quantifying, and studying affective states and subjective information.
Learn more in: General Awareness and Responses to COVID-19 Crisis: A Sentiment Analysis of Twitter Updates
3.
Part of social media analytics that uses analytical or computational techniques to determine the attitude or judgment of a speaker or a writer with respect to some topic, organization, brand, or products.
Learn more in: Business and Technology Trends in Social CRM
4.
Analysis
to identify emotions in some kind data as text, video, sound, and image.
Learn more in: Threat Emotion Analysis in Social Media: Considering Armed Conflicts as Social Extreme Events
5.
It is a natural language processing technique (NLP), which describes the
sentiment
orientation (positive, negative, neutral) underlying into the information.
Learn more in: Discovery of Sustainable Transport Modes Underlying TripAdvisor Reviews With Sentiment Analysis: Transport Domain Adaptation of Sentiment Labelled Data Set
6.
The
analysis
of language for positive or negative
sentiment
(without neutrality).
Learn more in: Frugal Living for Our Collective and Mutual #Bestlife on a Distributed and Global Electronic Hive Mind
7.
The process of computationally identifying and categorizing opinions expressed in a piece of text, especially in order to determine positive, negative, or neutral attitudes associated with test element.
Learn more in: Consumer Neuroscience: Evolution and Commercial Applications
8.
Identifying
sentiment
s, affect, subjectivity, and other emotional states in online text.
Learn more in: Using Big Data Opinion Mining to Predict Rises and Falls in the Stock Price Index
9.
Sentiment Analysis
is a subfield of artificial intelligence aimed at determining the polarity of opinions expressed by people. This type of
analysis
allows us to assign a positive, negative or neutral categorization to each document automatically.
Learn more in: Sentiment Analysis in Crisis Situations for Better Connected Government: Case of Mexico Earthquake in 2017
10.
Application of natural language processing, computational linguistics, and text analytics to identify and extract subjective information in text materials.
Learn more in: Sentiment Analysis in Supply Chain Management
11.
The process of computationally identifying and categorizing opinions expressed in a piece of text, especially in order to determine positive, negative, or neutral attitudes associated with test element.
Learn more in: The Future of Advertising: Influencing and Predicting Response Through Artificial Intelligence, Machine Learning, and Neuroscience
12.
The field of study that analyses people’s opinions,
sentiment
s, evaluations, appraisals, attitudes, and emotions towards products, services, organizations, individuals, issues, events, topics, and their attributes (Almuraih et al., 2020 AU98: The in-text citation "Almuraih et al., 2020" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. ).
Learn more in: The Stakes of Social Media: Analyzing User Sentiments
13.
Automatically analyses and classifies user’s emotions.
Learn more in: Deriving Business Value From Online Data Sources Using Natural Language Processing Techniques
14.
A form of semantics
analysis
to understand opinions, large sets of data can be collected from social media to understand user
sentiment
/opinion on a given subject.
Learn more in: Public Engagement and Policy Entrepreneurship on Social Media in the Time of Anti-Vaccination Movements
15.
It aims to determine the attitude of a writer on the topic. The attitude may be their judgment or evaluation, or the intended emotional communication on the topic.
Learn more in: Opinion Mining and Information Retrieval: Techniques for E-Commerce
16.
A branch of textual
analysis
that investigates the emotional state of a text, such as happy versus sad, based on linguistic features ( Pang and Lee, 2008 ).
Learn more in: Issues and Methods for Access, Storage, and Analysis of Data From Online Social Communities
17.
The process of computationally identifying and categorizing opinions expressed in a piece of text.
Learn more in: A Novel Method for Calculating Customer Reviews Ratings
18.
Sentiment Analysis
is a sub-research area of Natural Language Processing (NLP) studies. With
sentiment analysis
, also known as Opinion Mining, subjective language elements in oral or written texts about a particular subject can be interpreted.
Learn more in: Clubhouse Experience: Sentiment Analysis of an Alternative Platform From the Eyes of Classic Social Media Users
19.
Process of categorizing opinions expressed in text in order to understand consumers’ attitudes toward a topic.
Learn more in: Are Online Reviews Helpful for Consumers?: Big Data Evidence From Services Industry
20.
A form of semantics
analysis
to understand opinions, large sets of data can be collected from social media to understand user
sentiment
/opinion on a given subject.
Learn more in: Public Engagement and Policy Entrepreneurship on Social Media in the Time of Anti-Vaccination Movements
21.
The extraction of positive or negative opinions from unstructured text.
Learn more in: Ontology-Based Sentiment Analysis Model of Customer Reviews for Electronic Products
22.
Also known as opinion mining, it is a technique that allows classification and
analysis
of a large amount of texts to identify opinions and/or
sentiment
s in an automated form.
Learn more in: Sentiment Analysis, Social Media, and Public Administration
23.
Sentiment Analysis
is the technique that aids to recognize and classify the emotions and opinions of users in the communicated information, so that the opinion of the user for a certain utility or commodity can be determined as being positive, negative or neutral through NLP and content
analysis
.
Learn more in: Sentiment Analysis as a Restricted NLP Problem
24.
Sentiment analysis
is the systematic discovery, retrieval, quantification, and investigation of affective states and subjective information using natural language processing, text recognition, computational linguistics, and biometrics.
Learn more in: Applied Intelligence for Mental Health Detection: ManoVaidya – A Mental Health Therapist
25.
Is the application of natural language processing and computational linguistics to analyse textual data with the aim to associate the (individual or collective) opinions of authors towards a certain topic. In its simplest form, it focuses on sentences that signal positive, negative, or neutral attitudes and then derives a numerical statistic from the pattern matching in order to “quantitatively summarise” the written content.
Learn more in: Financial News Analytics
26.
A technique used to gain an overview of people’ opinion toward certain topics through text data.
Learn more in: Social Media-Based Data Collection and Analysis in Educational Research
27.
Process and summarize the public
sentiment
s to draw meaningful conclusion.
Learn more in: Analysis of Public Sentiments About Mega Online Sale Using Tweets on Big Billions Day Sale
28.
Sentiment analysis
is the interpretation and classification of emotions (positive, negative, and neutral) within text data using text
analysis
techniques.
Sentiment analysis
allows businesses to identify customer
sentiment
toward products, brands or services in online conversations and feedback.
Learn more in: Evolving Cyber Threats, Combating Techniques, and Open Issues in Online Social Networks
29.
The use of semi-automated techniques such as text mining, natural language processing and semantic rules to classify text according to its
sentiment
polarities or according to a
sentiment
scale.
Learn more in: Unraveling E-WOM Patterns Using Text Mining and Sentiment Analysis
30.
Capability to automatically classify user
sentiment
when performing a certain engagement action as, for example, negative, neutral or positive.
Learn more in: A Review of Tools for Overcoming the Challenge of Monitoring of Social Media
31.
It is the use of natural language process, text mining, and other techniques to study people’s opinion and emotion.
Learn more in: The Relationships Between Users' Negative Tweets, Topic Choices, and Subjective Well-Being in Japan
32.
The Process of analyzing various sources of unstructured online communication data to mine conversations online and to determine deeper context as they apply to a topic, brand, or theme.
Learn more in: A Conceptual Framework to Understand Online Destination Images: A Research Model Utilizing User-Generated Content Through Twitter
33.
A text
analysis
approach that automatically determines the emotion and polarity (negative, positive, neutral) in a text.
Learn more in: Understanding Tourist Perceptions and Expectations During Pandemic Through Social Media Big Data
34.
A process of analyzing and extracting the subjective opinions of texts.
Learn more in: Fighting Anti-Asian Hate in and After the COVID-19 Crisis With Big Data Analytics
35.
The activity of detecting polarities (positive, negative or neutral) or specific emotions from content.
Learn more in: E-Trading Decision Making: An Integrated Digital Marketing Approach With Theory and Cases
36.
Sentiment analysis
is the automated mining of attitudes, opinions, and emotions from text, speech, and database sources through natural language processing.
Learn more in: Approaches and Applications for Sentiment Analysis: A Literature Review
37.
The labeling of words and phrases as positive or negative (in a binary way) or in various categories of positive to negative (on a continuum).
Learn more in: Using Computational Text Analysis to Explore Open-Ended Survey Question Responses
38.
A process of computationally identifying and categorizing opinions expressed in a piece of text, especially in order to determine whether the writer's attitude towards a particular topic, product, etc. is positive, negative, or neutral.
Learn more in: What Are Basketball Fans Saying on Twitter?: Evidence From Euroleague Basketball's Final Four Event
39.
Artificial intelligence technique that detects emotions and
sentiment
s in social media.
Learn more in: Panic Station: Consumer Sentiment Analysis of the Evolving Panic Buying During the COVID-19 Pandemic
40.
The process of computationally identifying and categorizing opinions expressed in a text, especially in order to determine whether the writer's attitude towards a particular topic is positive, negative, or neutral.
Learn more in: The Integrated Tourism Analysis Platform (ITAP) for Tourism Destination Management
41.
The process of computationally identifying and categorizing opinions expressed in a piece of text, especially in order to determine positive, negative, or neutral attitudes associated with test element.
Learn more in: The Neuromarketing Revolution: Bringing Science and Technology to Marketing Insight
42.
Methodology for detecting emotions in content.
Learn more in: Using Sentiment Analysis for Evaluating e-WOM: A Data Mining Approach for Marketing Decision Making
43.
The task of discovering the underlying feelings expressed in a text. Methods are commonly classified by their scope, i.e. whether they consider aspects, sentences, or the entire document.
Learn more in: Deep Learning for Sentiment Analysis: An Overview and Perspectives
44.
Sentiment analysis
is the process of observing perspectives whether positive, negative, or neutral from written text in order to comprehend and evaluate reactions.
Learn more in: Developing Customer Engagement Through Artificial Intelligence Tools: Roles and Challenges
45.
A method to extract emotion information from text data.
Learn more in: Digital Transformation and Reimagined Brand Messages for Travelers in the Pandemic: Empirical Investigation on Twitter Data From Cruise Brands
46.
A process of uncovering subjective mental and emotional states in natural language.
Learn more in: Amplifying Participant Voices Through Text Mining
Find more terms and definitions using our
Dictionary Search
.
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