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The Only 5 Sentiment Analysis Tools Worth Knowing About

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Sentiment analysis tools are key to help you gauge how audiences perceive your brand. If you can get a handle on sentiment, you stand a better chance of boosting brand equity, and ultimately driving ROI.

What is a sentiment analysis tool?

Sentiment analysis tools are usually built into multifunctional news or social media monitoring tools. They help businesses detect the emotions and opinions expressed by their customers in text data.

Sentiment analysis tools use natural language processing (NLP) and AI to classify the emotions behind text-based content.

Artificial intelligence (AI) enables sentiment analysis to be undertaken at speed and at scale. It uses a sentiment analysis model to parse vast quantities of text data, like social media posts, customer reviews, or press content, and assigns a positive, negative, or neutral emotion to the input.

Some advanced sentiment analysis tools alert users to even more nuanced classifications such as controversy or harm. 

By quantifying positive and negative sentiment, brands can spot lucrative marketing opportunities and avoid brand-shattering PR. 

What are the benefits of using sentiment analysis tools?

Save time and money

Rather than sifting through thousands of social posts and reviews to understand your brand perception, you can use a sentiment analysis tool to scale that analysis for you.

Make better marketing and PR decisions

You can dedicate all the time you’ve saved on manual analysis to decision making and investing in the most rewarding strategies. For example, if the sentiment analysis tool shows negative sentiment surrounding your brand’s ESG initiative, you can launch a PR campaign to turn that around.

Improve product development

Tapping into opinions and customer feedback surrounding your products can help you refine your offering.

Transform customer service

Automatically analyzing the emotional subtext of customer conversations in your inbox with sentiment analysis tools can help you solve for service issues, before they escalate.

Avoid major PR disasters

Sentiment analysis tools can help you get ahead of PR fallout through crisis management, by alerting you to growing ire across your audience and customer base. 

The best sentiment analysis tools on the market

Sentiment analysis tools aren't foolproof. Sometimes emotional classifications will be off, and, like any AI based initiative, a human-in-the-loop approach is crucial. That said, we’ve compiled a list of the top 5 most trusted sentiment analysis tools, which won’t fail you.

1. SproutSocial: The customer service sentiment analysis software

Imagine being able to understand the sentiment behind every social media post, review, and direct message (DM). Well, that's exactly what SproutSocial offers with its AI sentiment analysis tools. 

SproutSocial allows users to undertake sentiment analysis across social and review platforms, as well as within their Smart Inbox, to analyze sentiment of customer feedback. 


Say you're a tech brand and you've just launched a new update, but a bug has accidentally been pushed live and it’s taken down the app. Since there’s no way to contact you through the app chat, users come to you via social media and leave negative customer feedback. SproutSocial’s sentiment analysis tools, within their Smart Inbox and Reviews Feed, would alert you to that snowballing negative sentiment.

Product features:

  • Uses AI to power its sentiment analysis tools

  • Builds AI sentiment analysis into customer feedback classifications via its Smart Inbox

  • Identifies emojis in text, and measures alongside sentiment analysis

  • Offers multilingual sentiment analysis tools

  • Gap analysis & side-by-side competitor comparisons of sentiment analysis

  • Measure sentiment across 

    • X/Twitter 

    • Facebook 

    • Instagram

    • Yelp

    • TripAdvisor

    • Glassdoor

  • Social posts are automatically assigned a sentiment, and users can set up their own rules.

2. CisionOne: The best sentiment analysis tools for news AND social media

When it comes to monitoring your brand's reputation, CisionOne is a true powerhouse. The sentiment analysis tool lets you analyze both social and media, while also giving you exclusive analysis of paywalled content from some of the most reputable news sources out there, like The Wall Street Journal, MarketWatch, and The New York Times.


Let's say you're a fashion company, and a major news outlet has just published an article about your latest product launch. With CisionOne's sentiment analysis tools, you can analyze the sentiment surrounding that article and gauge how it's being perceived by the public. 

Then, you can dive deeper and analyze the sentiment across different media types, such as online news, print, TV, and social media.

And it doesn’t end there. CisionOne's sentiment analysis tools also offers AI-powered risk score monitoring, which can help you stay ahead of potential crises by monitoring for controversial, emotional, or harmful content related to your brand.

Plus, the tool lets you dive deeper into specific negative news and customer satisfaction.

Product features:

  • AI sentiment trend timelines

  • Monitor the sentiment of single or multiple topics

  • Overall pi chart breakdowns of positive, neutral, and negative coverage

  • Slice and dice sentiment analysis across news media: online, print, TV, magazine, radio, and podcast media

  • Filter, segment, and analyze sentiment across social media: Facebook, X, and YouTube

  • Limit sentiment analysis to specific sources

  • Analyze sentiment through emoji count analysis

  • AI powered risk score monitoring across news media

    • Average risk score

    • Controversy

    • Emotionality 

    • Harm 

    • Spam

  • Self-rated sentiment analysis tools

  • Qualitative sentiment analysis tools

    • Content themes

    • Leading hashtags

3. Brandwatch: The enterprise social media sentiment analysis software

If you're looking to take your social media sentiment analysis to the next level, Brandwatch is the tool for you. Brandwatch can handle even the most complex language, slang, and dialects – and even helps users analyze the emotional context of emojis.

Brandwatch helps users dive deep into emotion distribution analysis, giving them insights into the prevalence of emotions like anger, disgust, fear, joy, and surprise surrounding their brand or its related topics. This level of granularity can be invaluable for crafting targeted marketing campaigns and addressing specific customer concerns.


A global brand, with a presence in multiple countries and languages, could use Brandwatch to analyze sentiment across over 40 languages, to ensure they’re capturing the full picture of how their brand is perceived worldwide.

Product features:

  • Sentiment analysis in over 40 officially supported languages, with the ability to classify sentiment in any language

  • Sentiment accuracy typically ranging between 60-75% for supported languages, though this can vary depending on the data source

  • Ability to manually override sentiment scores by selecting positive, neutral, or negative

  • Filtering feeds and conversation comments by sentiment, by selecting the desired sentiment in advanced filters

  • Analyzing the overall sentiment and emotion distribution for a search, as well as the prevalence of different emotions like anger, disgust, fear, joy, surprise, and sadness

  • State-of-the-art deep learning and natural language processing (NLP) techniques, including transfer learning, to provide more sophisticated sentiment analysis that can handle complex language, slang, and dialects

4. Lexalytics: The sentiment analysis API

Lexalytics is the unsung hero of the sentiment analysis world. You may not have heard of it yet, because it’s not a direct-to-consumer product, but this powerful text analysis API is the engine that powers many market-leading sentiment analysis tools, including Microsoft and Cision. Lexalytics also offers advanced NLP features like tokenization and part-of-speech tagging, which brands can use to improve their sentiment scoring, categorization, and theme analysis.


Product development teams working on a cutting-edge sentiment analysis solution may turn to Lexalytics to build a bespoke solution that aligns their customers’ needs and industry. This could involve adjusting the sentiment scale or incorporating industry-specific vocabulary.

Product features

  • The underlying technology and raw sentiment data that fuels other products on the market

  • Likely to be integrated by Product Development teams rather than marketers of PR professionals

  • Offers NLP features, including tokenization and part of speech tagging to enhance sentiment scoring, categorization, theme analysis and more.

  • Totally bespoke and can be adjusted to match your sentiment specifications – whether that’s based on scale, or industry-specific vocab

5. Brand24: The tool for analyzing the sentiment of your referrers

Last but not least, we have Brand24, a comprehensive social media monitoring and sentiment analysis tool. With Brand24, you can track sentiment across a wide range of platforms, including Twitter, Instagram, Facebook, videos, podcasts, forums, and web content. Brand24 also offers a reputation score gauge, which can give you a quick snapshot of how your brand is perceived overall. This can be especially useful if you need to identify potential issues or areas for improvement. But the most unique feature of Brand24 is its ability to help users decipher which of their referring sources are sending positive and negative sentiment their way.


Let's say you're a hotel chain, and you want to decipher how positively (or negatively) your traffic referrers are describing your brand. You can study the emotionality of those brand mentions with Brand24.

Product features:

  • Tracks sentiment breakdowns across, Twitter/X, Instagram, Facebook, videos, podcasts, forums, and web content

  • Sentiment over time

  • Topic analysis by sentiment

  • Sentiment of sources mentioning topics

  • Reputation score gauge

Challenges of Sentiment Analysis Tools

While sentiment analysis tools offer many benefits, they also come with some challenges:

Accuracy limitations

Sentiment analysis algorithms can struggle with sarcasm, idioms, and context-dependent language, leading to inaccurate classifications.

Data quality issues

The quality of sentiment analysis depends heavily on the quality and relevance of the input data. Noisy or irrelevant data can skew the results.

Lack of nuance

Most sentiment analysis tools classify text into broad categories like positive, negative, or neutral, failing to capture more nuanced emotions or sentiments.

Language barriers

Many tools are primarily designed for English text, and may perform poorly on other languages, especially those with complex grammar or writing systems.

Ethical Considerations

As sentiment analysis tools become more prevalent, it's important to consider the ethical implications:

Privacy concerns

Analyzing sentiment from public data like social media posts raises privacy issues, especially if the data is used for targeted advertising or other purposes without user consent.

Bias and discrimination

Sentiment analysis algorithms can perpetuate societal biases present in the training data, leading to unfair or discriminatory treatment of certain groups.

Manipulation and misuse

Sentiment analysis could potentially be used to influence public opinion or manipulate emotions on a large scale, raising concerns about the ethics of such practices.

Future Trends in sentiment analysis

The field of sentiment analysis is rapidly evolving, with several key trends emerging:

Multimodal analysis

Tools are beginning to incorporate sentiment analysis from multiple data sources, such as text, images, audio, and video, for a more comprehensive understanding.

Aspect-based sentiment analysis

Instead of classifying sentiment at the document level, newer techniques aim to identify sentiment towards specific aspects or features of a product or service.

Explainable AI

There is a growing focus on developing sentiment analysis models that are transparent and can explain their reasoning, increasing trust and accountability.

Transfer learning

Leveraging pre-trained language models and transfer learning techniques can improve the accuracy and adaptability of sentiment analysis models, especially for low-resource languages or domains.

So, there you have it – the top five sentiment analysis tools that are worth paying attention to. Whether you're a small business or a global enterprise, these tools can provide you with the insights you need to stay ahead of the competition and make sentiment analysis decisions that drive success.

Author Bio
Marcelo Javelly
Marcelo Javelly
SEO and Social Listening Specialist

Marcelo is an SEO and Social listening expert with 8+ years of experience across various industries and joined Cision in 2023. Based in Copenhagen, he is our in-house specialist for all things related to social listening.