The BigFive Sentiment Analysis API uses advanced machine learning algorithms to analyze text and determine the emotions and personality traits expressed within it. It can classify text into five main categories: Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism, and provide the results in a structured format.
{"text":"I am 30 years old man. I studied physics and currently work as a software engineer. I am married and have a couple of kids. What else I can tell... I am open to new experiences and like to chat. I am being nasty sometimes.","inventories":["big5"],"scoring":{"big5":{"agreeableness":{"quantile":0.394,"score":-0.628,"confidence":0.095,"confidence_text":"low"},"conscientiousness":{"quantile":0.473,"score":-0.115,"confidence":0.012,"confidence_text":"very low"},"extraversion":{"quantile":0.585,"score":0.424,"confidence":0.133,"confidence_text":"low"},"neuroticism":{"quantile":0.568,"score":0.371,"confidence":0.116,"confidence_text":"low"},"openness":{"quantile":0.614,"score":0.59,"confidence":0.059,"confidence_text":"low"}}},"lang":"en"}
curl --location --request POST 'https://pr213-testing.zylalabs.com/api/950/bigfive+sentiment+analysis+api/772/check+bigfive' --header 'Authorization: Bearer YOUR_API_KEY'
--data-raw '{
"text": "I am 30 years old man. I studied physics and currently work as a software engineer. I am married and have a couple of kids. What else I can tell... I am open to new experiences and like to chat. I am being nasty sometimes.",
"inventories": [
"big5"
],
"lang": "en"
}'
After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the BigFive Sentiment Analysis API simply include your bearer token in the Authorization header.
| Header | Description |
|---|---|
Authorization
|
Required
Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.
|
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The BigFive Sentiment Analysis API is a powerful tool that uses advanced machine learning algorithms to analyze text and determine the emotions and personality traits expressed within it. The API is based on the Big Five personality traits model, which is widely used in psychology and social science research, and it classifies text into five main categories: Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism.
One of the key benefits of this API is its ability to provide a detailed analysis of text, identifying not only the overall sentiment but also the specific emotions and personality traits expressed within it. This allows developers to gain a deeper understanding of the text and the people behind it.
The API can be used on a wide range of text, including social media posts, customer reviews, survey responses, and much more. It can be useful in various use cases such as analyzing customer feedback, understanding customer preferences and identifying patterns in social media posts.
The API can be easily integrated into any application, and it can be accessed via a simple API call. It returns the results in a structured format, making it easy for developers to use the data in their applications.
Overall, the BigFive Sentiment Analysis API is a powerful tool that can help developers gain a deeper understanding of the text and the people behind it. Providing a detailed analysis of text based on the Big Five personality traits model can help developers create better and more personalized experiences for their users.
Pass a text in a JSON and the API extracts Big Five psychological traits from the text written by the person. These include Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism also known as OCEAN.
Social Media Monitoring: The BigFive Sentiment Analysis API can be used to analyze social media posts and determine the emotions and personality traits expressed by users, providing valuable insights into consumer sentiment and behavior.
Customer feedback analysis: The API can be used to analyze customer feedback from surveys, reviews and other sources, helping companies to understand customer preferences and identify areas for improvement.
Recruiting and HR: The API can be used to analyze job applicants' resumes and cover letters to identify the personality traits that best match the requirements of a specific job.
Market Research: The API can be used to analyze text data from focus groups, interviews and surveys to identify patterns in consumer behavior and preferences.
Content creation: The API can be used by content creators to evaluate the effectiveness of their written content, by identifying the emotions and personality traits that resonate with their audience.
Healthcare: The API can be used to analyze patient feedback and determine the emotions and personality traits that may be associated with certain symptoms or conditions, providing valuable insights for healthcare professionals.
Besides API call limitations per month, there are no other limitations.
The "Check BigFive" endpoint returns a JSON object containing the extracted Big Five personality traits (Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism) along with quantile scores, confidence levels, and descriptive confidence text. The "POST JSON to XML" endpoint returns an XML document wrapped in a 'root' tag, containing structured data based on the input JSON.
For the "Check BigFive" endpoint, key fields include "text" (input text), "inventories" (trait categories), and "scoring" (detailed scores for each personality trait). In the XML response, key fields depend on the input data structure, typically including various medical or personal attributes.
The "Check BigFive" endpoint returns data in JSON format, structured with nested objects for scoring and traits. The "POST JSON to XML" endpoint returns data in XML format, organized under a 'root' tag with child elements representing various data points.
The "Check BigFive" endpoint accepts a single parameter: a JSON object containing the text to analyze. The "POST JSON to XML" endpoint accepts a JSON object up to 1MiB in size. Users should ensure their input adheres to these specifications for successful processing.
The response from the "Check BigFive" endpoint is organized into a main object containing the input text, inventories, and a scoring object with detailed trait scores. The XML response is structured hierarchically, with elements nested under the 'root' tag, reflecting the input data's structure.
Typical use cases include analyzing social media sentiment, evaluating customer feedback, assessing job applicants' personality traits, conducting market research, and enhancing content creation strategies. Each use case leverages the insights provided by the Big Five personality traits.
Users can utilize the returned data by interpreting the personality trait scores to inform decisions, such as tailoring marketing strategies or improving user engagement. The confidence levels and descriptive text help gauge the reliability of the analysis, guiding further actions.
The BigFive Sentiment Analysis API employs advanced machine learning algorithms trained on diverse datasets to ensure accuracy in personality trait extraction. Continuous model evaluation and updates help maintain data quality and relevance, enhancing the reliability of the insights provided.
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