Quickly extract and analyze the sentiment associated with specific entities in your text data with just a few simple steps!
Entity Sentiment Analysis (or Targeted Sentiment Analysis) is an advanced form of Traditional Sentiment Analysis that goes beyond analyzing the overall sentiment of a piece of text. Instead, it focuses on identifying and analyzing the sentiment associated with specific entities mentioned in the text, such as people, products, organizations, or topics.
Entity Sentiment Analysis uses both NLP and Sentiment Analysis to identify the sentiment (positive or negative) conveyed about entities in the text, offering a more detailed and finely-tuned comprehension of the sentiments embedded within the text.
After detecting the entities referenced in a document and which portions of the document discuss each item, it reliably predicts the attitude conveyed about each unique entity in the text, even when the mood about each is different.
While Traditional Sentiment Analysis provides an overall sentiment score for a piece of text, Targeted Sentiment Analysis delves deeper by analyzing sentiment associated with specific entities within the text. Choosing between the two techniques depends on your project goals and the level of detail you require to make informed decisions or gain valuable insights from the text data.
Our standardized API allows you to use different providers on Eden AI to easily integrate Entity Sentiment Analysis APIs into your system.
Amazon Comprehend is a natural-language processing (NLP) service that employs machine learning to analyze text data for insights. Targeted Sentiment is a new API from Comprehend that gives more detailed sentiment insights by recognizing the sentiment (positive, negative, neutral, or mixed) towards entities within the text.
The API can identify various entity types, including PERSON, LOCATION, ORGANIZATION, FACILITY, BRAND, COMMERCIAL_ITEM, MOVIE, MUSIC, BOOK, SOFTWARE, GAME, PERSONAL_TITLE, EVENT, DATE, QUANTITY, etc., making it versatile for analyzing different types of content.
The Google Cloud Natural Language API performs natural language processing (NLP) to evaluate and extract sentiment from text data. The results can show if a mention of the entity is favorable, negative, or neutral. Additionally, this API can locate things in text (such as persons, places, and organizations) and provide information about their emotions.
Using an Entity Sentiment API offers a range of benefits that enhance various aspects of text data processing and analysis. Some of the key advantages include:
Entity Sentiment APIs have a wide range of uses across various industries and applications. Here are some common use cases:
The sentiment surrounding certain people, companies, or goods referenced in social media postings, comments, and reviews may be tracked and analyzed using entity sentiment APIs. This aids businesses and people in determining how the general audience feels and perceives their products.
These APIs may be used by businesses to evaluate customer feedback and reviews to learn how customers feel about their goods and services. This knowledge may direct efforts to enhance products, develop marketing plans, and provide customer service.
Entity Sentiment APIs may be used by media companies and news organizations to determine how the public feels about various entities that are referenced in news pieces, enabling more data-driven reporting and analysis.
Entity Sentiment APIs may be used by academics and political analysts to examine how the general public feels about certain politicians, policies, and topics. This can help in polling the public and determining voter sentiment.
Entity sentiment analysis may be used by media streaming services and content providers to suggest material to consumers based on their sentiment preferences, enhancing user engagement and happiness.
To start using Entity Sentiment you need to create an account on Eden AI for free. Then, you'll be able to get your API key directly from the homepage and use it with free credits offered by Eden AI.
When implementing Entity Sentiment on Eden AI or any other platform, it's essential to follow certain best practices to ensure optimal performance, accuracy, and security. Here are some general best practices for Entity Sentiment on Eden AI:
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