Summary: Using a text sentiment analysis tool, you can find out which competitor is receiving positive mentions and also learn about your audience through social mentions. Thus, by analyzing their tone or language, you can also incorporate the same in your marketing strategy to improve your brand image.
Maintaining a good brand reputation is important for the success of any organization, big or small. For only with a positive brand reputation can you close more sales, build customer loyalty, and improve customer experience.
To attain the same, as the very first step, you need to keep a close tab on your brand image on different social media platforms. Sentiment analysis tools are designed to help you do just that. These tools, also commonly referred to as sentiment detection tools, analyze emails, reviews, chat transcripts, posts, mentions, and comments made on social media to identify the sentiments expressed by your customers about your product, service, and brand. marketing campaigns and boost sales.
Intrigued much? Let’s learn more about these tools in detail below, because why not?
Sentiment analysis utilizes machine learning (ML) models and natural language processing (NLP) techniques to perform real time customer sentiment analysis. The goal is to determine whether sentiments expressed in any text are good or bad. Here’s how sentiment mining works…
Step 1: Data Collection
The process begins by gathering text data from sources like social media posts, reviews, or surveys.
Step 2: Keyword Identification
The sentiment analyzer tool identifies specific keywords and phrases that convey the main meaning behind the content.
Step 3: Text Preprocessing
The content then undergoes a thorough cleaning process. This involves removing noise such as punctuation, URLs, emojis, and special characters, converting all text to lowercase for consistency, and normalizing formats.
The content is further broken down into tokens (words or phrases), and common stop words like ‘the’ or ‘and’ are removed because they do not add meaningful value. Finally, stemming or lemmatization is applied to reduce words to their base form, say ‘running’ is made ‘run’, making the text easier for algorithms to interpret.
Step 4: Feature Extraction
The processed text is converted into numerical representations using methods like Bag-of-Words, TF-IDF, or word embeddings.
Step 5: Sentiment Modeling
The text is then analyzed using NLP and ML techniques through three main approaches. The first approach is lexicon analysis that uses sentiment dictionaries. The second one involves machine learning models like Naive Bayes or SVM trained on labeled data. And the third one uses advanced deep learning models such as BERT for context-aware sentiment detection.
Step 6: Sentiment Scoring
The model assigns a score or polarity (positive, negative, neutral). Advanced systems may also perform aspect-based sentiment detection to evaluate opinions on specific features.
Step 7: Handling Nuances
The system handles tricky language patterns like negation (e.g., “not good”), sarcasm, slang, and terms specific to certain industries.
Step 8: Evaluation & Visualization
Finally, the model’s performance is validated using metrics like accuracy and F1-score, and results are visualized through dashboards for useful insights.
Here are some of the best sentiment mining tools, both free and paid, you can make use of to know your brand’s standing on social media…
| Sentiment Detection Tool | Best For | Real Time |
|---|---|---|
| Brandwatch | Large brands needing social listening & consumer insights | Yes |
| Sprout Social | Social teams & social media management | Yes |
| Google Cloud | Developers integrating NLP via API | Yes |
| IBM Watson | Deeper tone/sentiment & text analytics | Yes |
| SentiSum | VoC analytics for support, CX, tagging & automations | Yes |
| Lexalytics | Complex text mining with customizable NLP | Yes |
| Qualtrics | Surveys + social listening + CX dashboards | Yes |
| Talkwalker | Global trends & consumer intelligence | Yes |
| Brand24 | Quick monitoring & AI sentiment for SMBs | Yes |
| Medallia | Enterprise CX with omnichannel text analytics | Yes |
Brandwatch is a real-time sentiment analysis tool and social listening platform that monitors conversations across social media, blogs, forums, and news sites. It uses AI-powered natural language processing to classify mentions as positive, negative, or neutral, and supports image and video sentiment detection.
With real-time dashboards, trend forecasting, and influencer identification, it helps brands understand customer sentiments and make better decisions for marketing and engagement.
Brandwatch
Starting Price
Price on Request
Key Features of Brandwatch:
Pro and cons of Brandwatch:
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Brandwatch Pricing & Plans: Price on request
Sprout Social is social media management platform that includes sentiment analysis to evaluate audience emotions in real time. It analyzes comments, mentions, and messages across multiple networks to help brands track public perception, identify trends, and respond accordingly. This functionality helps improve customer engagement and the overall reputation of a brand.
Key Features of Sprout Social:
Pro and cons of Sprout Social:
Pros
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Sprout Social Pricing & Plans:
| Plan | Price |
|---|---|
| Standard | $199/seat/month |
| Professional | $299/seat/month |
| Advanced | $399/seat/month |
| Enterprise | Price on request |
Google Cloud Natural Language API is a smart machine learning tool that conducts text sentiment analysis in detail. It can find emotions, check sentence structure, and identify important topics or keywords to show whether the text is positive or negative and how strong those feelings are. Businesses, as such, use it to analyze reviews, social media posts, and other content to improve customer experience and make informed decisions.
Key Features of Google Cloud Natural Language API:
Pro and cons of Google Cloud Natural Language API:
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Google Cloud Natural Language API Pricing & Plans:
| Feature | Free Tier | Price per 1,000 Characters |
|---|---|---|
| Entity Analysis | First 5,000 units/month | $0.001 |
| Sentiment Analysis | First 5,000 units/month | $0.001 |
| Syntax Analysis | First 5,000 units/month | $0.0005 |
| Entity Sentiment | First 5,000 units/month | $0.002 |
| Content Classification | First 5,000 units/month | $0.002 (first 30K units), then tiered down to $0.0001 |
IBM Watson provides sentiment detection through its Tone Analyzer. Using which, it understands the tone and emotions in written text. It looks at words and phrases to figure out if the text sounds happy, sad, confident, angry, or neutral. Brands use it to analyze emails, chats, and social media posts so they can understand customer feelings and respond in the right way.
Key Features of IBM Watson Tone Analyzer:
Pros
Cons
IBM Watson Tone Analyzer Pricing & Plans:
| Plan | Price per API Call |
|---|---|
| Lite (2,500 API calls/month) | $0/API Call |
| Plus | $0.0088/API Call |
| Enterprise | Price on request |
SentiSum is a customer feedback analysis tool that uses AI to understand what customers are saying and how they feel. It automatically reads reviews, support tickets, and survey responses to find common issues and emotions. Brands primarily use it to spot trends and make better decisions based on real customer sentiment analysis.
Key Features of SentiSum:
Pro and cons of SentiSum:
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SentiSum Pricing & Plans:
| Plan | Price |
|---|---|
| Pro | $3000/month |
| Enterprise | Price on request |
Lexalytics Semantria is a text analytics solution that works with large volumes of data from sources like surveys, reviews, and social media. It makes use of NLP for sentiment analysis, along with themes and key topics.
Businesses put it to use in a bid to uncover insights hidden in customer feedback, helping them improve products and services.
Key Features of Lexalytics Semantria:
Pro and cons of Lexalytics Semantria:
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Cons
Lexalytics Semantria Pricing & Plans: Price on request
Qualtrics XM is an experience management platform that helps organizations collect and analyze feedback from customers, employees, and other stakeholders. It doesn’t just collect feedback; it interprets it.
Using sentiment mining, it identifies emotions and intent behind responses, helping businesses see what people truly feel. This insight powers smarter decisions and stronger relationships.
Qualtrics XM
Starting Price
Price on Request
Key Features of Qualtrics XM:
Pro and cons of Qualtrics XM:
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Qualtrics XM Pricing & Plans: Price in request
Talkwalker is a social listening and analytics platform that tracks what people say about brands across social media, news, blogs, and forums. It uses AI to spot sentiment, trending topics, and spikes in conversation, so you can see what’s driving buzz and why. In that regard, it acts like an early-warning system and insight engine for PR, marketing, and customer experience teams.
Key Features of Talkwalker:
Pro and cons of Talkwalker:
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Talkwalker Pricing & Plans: Price on request
Brand24 is social listening tool that l that tracks mentions of your brand across the web and social media. It uses sentiment analysis to tag comments as positive or negative in real time, making it simple for small teams to monitor reputation. Its NLP-powered engine even handles platforms like X and TikTok.
Brand24
Starting Price
$ 199.00
Key Features of Brand24:
Pro and cons Brand24:
Pros
Cons
Brand24 Pricing & Plans:
| Plan | Price |
|---|---|
| Individual | $149/month |
| Team | $249/month |
| Pro | $299/month |
| Business | $499/month |
| Enterprise | Starts from $999/month |
Medallia collects comments, reviews, and survey responses from multiple channels and uses AI-driven sentiment analysis to uncover how customers feel. Beyond just measuring sentiment, Medallia helps businesses spot patterns, predict behavior, and improve experiences in real time.
Medallia
Starting Price
Price on Request
Key Features of Medallia:
Pro and cons of Medallia:
Pros
Cons
Medallia Pricing & Plans: Price on request
Using sentiment analytics tools can help your organization in multiple ways, such as…
Conclusion
Sentiment analysis tools can be leveraged to perform multiple tasks. From monitoring social media and analyzing product reviews to performing competitor research, these tools can help you enhance your brand image in ways aplenty.
So, get in touch with the Techjockey product team today itself and lay your hands on the best sentiment analyzer to give your business a reputation-based boost like no other.
A sentiment analysis tool is an AI software that analyzes the text data to identify positive, negative, and neutral sentiments in the content shared by your customers across different web channels.
Natural language processing is used in sentiment analysis to identify the tone or sentiments in any content related to a person, entity, product, etc.
There are three main methods used for sentiment analysis including Lexicon Based Approach, Hybrid Approach, and Machine Learning Approach. The best method to consider is Hybrid method where you can leverage both other methods for text analysis.
The three main sentiment analysis methods are Lexicon Based Method, Machine Learning Method, and Hybrid Method.
Sentiment analysis is a subset of Natural Language Processing (NLP). It is a kind of data mining technique that tries to understand and measures customers opinions and stances via NLP.
Sentiment analysis is used to analyze different types of text data which might include public mentions, comments, reviews, press releases, and so on.
The simplest sentiment analysis can be done using a scored word list. For example, you can create a list of words that are scored between +5 and –5. Next, you can split a given content into distinct words and compare them with the word list to get the final sentiment score.
The first step in sentiment analysis is to choose the type of content for which you want to perform the analysis. For example, you can choose from analyzing conversation threads, comments, or mentions.
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