Features of Sentiment Analysis

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Table of Contents ● What is Sentiment Analysis? ● What are key sentiment analysis features? ● An API with the best sentiment analysis features

10 Features of sentiment analysis To Look Out For www.repustate.com

Sentiment analysis is a type of data analytics that deals specifically with text that expresses various forms of emotions - from love to hate. An emotion mining API with its precision-laden sentiment analysis features prompts the digital transformation of organizations through their big data. Big data needs to be leveraged and so it must be mined for insights that companies can use to formulate solutions and strategies for growth. After all, to be data-driven does not just mean data-gathering but truly understanding it as well.

What is Sentiment Analysis?

Some of the most useful insights are opinions and feelings that customers and consumers express about their purchase journey and experience. The process of extracting and scoring this type of customer data is called sentiment analysis or sentiment mining.

When applied, sentiment analysis rates chunks of such text data as positive, neutral or negative. It empowers you to understand your customers, employees, or patients better - regardless of your industry or countries. This is how a good multilingual sentiment analysis software can help boost your business intelligence and build brand reputation.

What are key sentiment analysis features?

Key features that are essential in a sentiment monitoring tool are multilingual efficacy, precise aspect-based sentiment analysis, named entity recognition, and an effective visualization dashboard.

The following list has more details on the features and benefits you should look at, if you are in the market for a sentiment analysis tool.

How is sentiment analysis on reviews done?

1. Data Gathering:

Gather and prepare your data that you want to analyze whether it’s internal (customer feedback) or external data (reviews from rating sites). To prepare the data for text analysis, all you need to do is put it into a CSV or XLS document format.

2. Apply Review Sentiment Analysis API:

Run your input data through your sentiment analytics API. It will quickly return sentiment scores for each relevant review topic, aspect, or entity ranging from -1 for negative emotions, 0 for neutral feelings, and 1 for positive sentiment.

3. Sentiment Analysis Dashboard:

Once you receive the sentiment scoring, you can use various different data visualization tools like Power BI, Tableau, or Repustate’s Sentiment analysis dashboard to quickly turn your data into visual reports. These reports are made up of charts, graphs and tables to discover trends, patterns, and actionable insights in your data.

An API with the best sentiment analysis features An API with the best sentiment analysis featuresRepustate’s sentiment analysis engine is supported by the world’s most efficient named entity recognition (NER). The intuitive sentiment analysis solution comprises all the top ten sentiment analysis features noted above and is driven by its NER that is the foundation of the engine’s deep semantic search capability. Because of this, the model gives a stellar performance in the four most important areas - accuracy, granularity, languages, and speed.

The very fact that our sentiment analysis API supports more than 23 languages natively, tells you how painstakingly the corpus for each language has been manually curated and tagged by our data scientists over a decade, and the model trained to achieve more than an 85% accuracy rate.

Understand your data, customers, & employees with 12X the speed and accuracy.

Thank you!

Visit: www.repustate.com to learn more