What Is A Sentiment Analysis Tool?
A sentiment analysis tool is AI software that automatically analyzes text data to help you quickly understand how customers feel about your brand, product, or service. Sentiment analysis tools work by automatically detecting the emotion, tone, and urgency in online conversations, assigning them a positive, negative, or neutral tag, so you know which customer queries to prioritize. There are many sentiment analysis tools available, but not all are equal. Some are a lot easier to use than others, while some require an in-depth knowledge of data science.
What Is A Sentiment Analysis Tool?
A sentiment analysis tool is AI software that automatically analyzes text data to help you quickly understand how customers feel about your brand, product, or service.
Sentiment analysis tools work by automatically detecting the emotion, tone, and urgency in online conversations, assigning them a positive, negative, or neutral tag, so you know which customer queries to prioritize. There are many sentiment analysis tools available, but not all are equal. Some are a lot easier to use than others, while some require an in-depth knowledge of data science.
Here is a list of the top 10 sentiment analysis tools:
- Aspect-Based Analysis
1. Aspect-Based Analysis
Aspect-based sentiment analysis focuses on certain features (aspects) of your product or service. With this approach to sentiment analysis, you can determine if something positive, negative, or neutral was said and about which feature.
Brandwatch Consumer Research gives access to deep consumer insights from 100 million online sources and over 1.4 trillion posts. This figure increases by 496 million posts every day.
Brandwatch employs a rules-based process to better understand the ways context can affect sentiment. It takes all the words and phrases that imply positive or negative sentiment and applies rules that consider how context might affect the tone of the content. Carefully crafted rules help the software know phrases that are positive versus those that are negative. Users can redefine sentiment if they believe that it has been wrongfully categorized.
- Advanced AI: AI-powered search with custom classifiers and image analysis.
- Consumer Research: Get instant access to the world’s largest archive of consumer opinions including more than 1.4 trillion posts dating back to 2008!
- Powerful Analytics: A flexible UI with 50+ live visualizations.
- Connected Solutions: Integrations with a full suite of intelligence products.
Lexalytics’s Semantria API lets you set up sentiment analysis tools in the cloud. If you’re looking for an on-premise solution, tailored towards data scientists and architects who want full access to the technology or who need on-premise deployment for security reasons, look no further than Lexalytics Salience.
Whichever infrastructure you choose, you’ll have access to the platform’s powerful NLP sentiment analysis system, which can be tweaked to your specific needs, though you’ll need a data science background to understand how the Lexalytics API works.
Repustate’s sentiment analysis software can detect the sentiment of slang and emojis to determine if the sentiment behind a message is negative or positive. Repustate offers a free trial so you can try the tool to see if it really suits your needs.
Customize the API to identify one of 23 languages, and train sentiment analysis models to recognize alternative meanings of words, to gain even more accurate sentiment insights.
Clarabridge provides sentiment analysis through its CX Analytics and CX Social modules. The platform monitors everything you’d need, including social media platforms, forums, blogs, review sites, and news sites, analyzing engagement rate, response time, sentiment, and growth of mentions. Clarabridge uses an 11-point scale to index sentiment and takes context, grammar, industry, and the source of the data into account during scoring.
- Multiple Sources: Collect data from hundreds of sources like calls, emails, chats, surveys, social interactions, ratings and reviews, or forums.
- Customer Effort: Understand how much effort your customers are putting in through analysis of the keywords used in feedback.
- Sentiment Analysis: Combining lexical and grammatical approaches to analyze sentiment at the clause level.
- Pre-Built Industry Categorization: Group text data into related buckets that make sense for your industry.
- Emotion Analysis: Examine and understand the motions customers feel when engaging with your company, products, or service.
- Intent Detection: AI-powered semantic analysis strategies can identify 21 different kinds of intents like requests, praise, cries for help, churn, and even legal disclosures in customer feedback.
Perform multilingual sentiment analysis using MeaningCloud’s Sentiment Analysis API. This online tool runs aspect-based sentiment analysis to decide whether specific topics are mentioned in a positive, negative, or neutral way. Additionally, you can define a dictionary to include any specific vocabulary that you might use in your field. Some of MeaningCloud’s best features are the detection of global sentiment (a general view of what the customer expressed in a certain text), identification of opinion versus fact, and spotting sentiment within each sentence of a text.
MonkeyLearn hosts a suite of text analysis tools, including a ready-to-use sentiment analysis tool, with exceptional accuracy. MonkeyLearn’s products easily integrate with tools like Zendesk and Google Sheets. If you know how to code, you’ll be able to use MonkeyLearn API to connect sentiment analysis tools to your stack. You might also want to build a customized sentiment analysis model without writing a single line of code. The advantage of building your own sentiment analysis tool is that it will be more accurate.
Lexalytics focuses more on sentiment analysis and less on brand mentions than many other tools included here. The Lexalytics Intelligence Platform targets businesses that process high volumes of text data (30,000+ docs/month), need on-premise security; to run the system behind your firewall, or want deep access to tune and configure your text analytics.
It recognizes that sentiment analysis is vital for social media monitoring (SMM). Lexalytics uses natural language processing (NLP) and machine learning to transform mountains of hashtags, slang, and poor grammar into structured data and valuable insights. The platform analyzes social text data to understand the conversations surrounding products, brands, people, and services.
RapidMiner provides a data science platform to deliver transformational business impact. This includes text mining, where you can use insights from unstructured data to improve marketing, product development, risk management, and more. Online reviews, social media chatter, call center transcriptions, claims forms, research journals, patent filings, and many other sources all become rich resources that you can tap through data science to advance your business and organizational mission.
Understand the severity and impact of news events and stories in real time with Aylien News API. Detect sentiments across news stories and dive deeper into topics with aspect-based sentiment analysis.
The text analysis platform also allows you to build your own models hassle-free, and you don’t need to know a lot about machine learning or NLP to get started.