Social Media Sentiment Analysis: How To Perform

In this guide, we’ll explore the what, why and how of social media sentiment analysis so you can unlock valuable insights and understand your customers’ emotions and opinions.

Despina SinghAishwarya Suresh
June 10, 2024
7 min read

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Table of Contents

What is social media sentiment analysis?

Social media sentiment analysis unlocks the essence of what people express about your brand or business across social platforms. It goes beyond tallying mentions or comments, delving into the realm of emotions and opinions.   

By analyzing social sentiment, we gain valuable understanding to strengthen our social media monitoring plan, enabling us to grasp how people perceive our products, services and brand. It's like peering into the collective customer conversation, making sense of how people talk about your brand and whether their comments are positive, negative or neutral.

Types of sentiments:

When it comes to emotions it can be quite complex and might not fit into neat categories. However, we can broadly categorize sentiments.   

Whether it's a brand mention or a conversation, they usually carry a specific sentiment: positive, negative or neutral.   

Here’s what some terms might look like for each sentiment:   
Positive: fantastic, excellent, delightful, wow, impressive, enthusiastic  
Negative: terrible, awful, horrible, frustrating, annoying, upsetting, ugh  
Neutral: acceptable, average, okay, moderate, satisfactory, ordinary 

Role of sentiment analysis in social media  

Social media sentiment analysis plays a vital role in grasping the significance of your brand's presence online. As mentioned earlier, just counting the number of social mentions won't give you the full scoop. It's crucial to delve deeper and uncover the true sentiments expressed by people.   

While a substantial number of mentions may initially appear impressive, if they mainly convey negativity, the narrative changes completely.  

Sentiment analysis lets you uncover the emotions and opinions behind those mentions. This knowledge empowers you to understand public perception and take actions to improve your brand's reputation and address any issues head-on. 

In 2020, companies claimed a 54% adoption rate for technologies that analyze customers' sentiment from reviews or social media.  By the end of 2023, this figure is projected to soar past 80%, showcasing a remarkable surge in implementation. 
Source: Bain & Company  

Top 4 benefits of social media sentiment analysis 

Social media sentiment analysis offers numerous benefits that can have a positive impact on your organization.

  • Brand monitoring and reputation management: Proactively track and manage brand reputation by analyzing sentiment, addressing negative feedback, leveraging positive sentiment and building strong audience relationships  

  • Crisis management and public perception: Effectively manage crises by assessing public reactions, addressing concerns, taking appropriate actions and shaping public perception through timely responses and transparently addressing issues  

  • Audience understanding and engagement: Analyzing social media sentiment allows you to understand and engage with your audience, creating resonant messaging and fostering stronger connections for customer satisfaction  

  • Strategic decision-making and competitive advantage: Gain a strategic advantage by informing decisions, enhancing products, aligning strategies with trends, identifying opportunities, anticipating customer needs and staying ahead in a dynamic landscape  

These benefits testify to the potential of social media and can drive meaningful outcomes for your brand and audience. 

But how to get all these benefits? Try social listening! Protect your brand with real-time crisis alerts, dive into extensive data across 30+ channels, capture every relevant conversation and benchmark against competitors — all in one powerful platform — Sprinklr Insights

Sprinklr Insights dashboard

Start your journey towards a transformed brand strategy with a demo of Sprinklr Insights. 

Key challenges of social media sentiment analysis 

Social media sentiment analysis has its fair share of challenges. 

Let's explore the key obstacles that researchers and analysts face when attempting to uncover the sentiments hidden within the digital tapestry of social media platforms. 

  • Noisy and unstructured data: Sentiment analysts struggle with social media's noisy and unstructured data, full of short, informal and fragmented texts with context, sarcasm, slang, abbreviations, misspellings, emoticons and emojis 

  • Ambiguity and context-dependence: Identifying sentiment in social media is a tough challenge due to varied posts lacking explicit cues, context, author perspective and intended audience 

  • Handling sarcasm and irony: Sophisticated ML algorithms are needed to detect figurative language like sarcasm and irony in social media, as sentiment analysis models mainly rely on literal interpretations  

  • Domain-specific challenges: Applying sentiment analysis models trained on general datasets to specific domains or industries poses challenges due to the unique vocabulary, jargon and sentiment patterns of each domain, requiring the construction of domain-specific models or adaptation of existing models for accurate results. That’s where a Generative AI-enriched model enters the picture and derives insights from relevant structured and unstructured conversations happening across the web to deliver domain-specific sentiment insights to the right stakeholder at the right time. 

Sprinklr AI for Social Publishing & Engagement

Now that we have explored some challenges of social media sentiment analysis, let's delve into the next area of our guide.

How to perform sentiment analysis in 3 steps 

Performing sentiment analysis on social media platforms can unlock valuable insights into public opinion and brand perception.   

Step 1: Stay in the loop with conversations about your brand

It's important for businesses to monitor their mentions and hashtags on platforms like X, Instagram, Facebook and TikTok. This way, you can make the most of positive feedback and address any criticism promptly.  

Don't forget to keep an eye on third-party sites and review forums like Google Reviews, Reddit and Yelp.  
If you're in e-commerce, pay attention to on-site reviews from loyal customers — they offer valuable insights.  
💡 Pro Tip: Monitoring all these platforms manually takes time. Use Sprinklr, a social listening tool that collects and monitors real-time social media data, performs sentiment analysis, identifies trends, offers customization options and provides reporting and analytics capabilities, including tracking relevant keywords associated with your brand, even without direct tagging. 

Data on social media intelligence and brand mentions across multiple channels via Sprinklr platform

Step 2: Choose the right terms for sentiment analysis

Effective sentiment analysis relies on accurately categorizing positive and negative mentions. 

To achieve this, it's essential to identify relevant terms that reflect customer sentiment. Some terms may be straightforward, while others might be specific to your industry.
Divide your sentiment terms into positive and negative groups. As earlier mentioned, here's an example to illustrate:


excellent, love, kudos, fantastic, perfect, appreciate 


terrible, hate, disappointing, awful, poor, avoid 


acceptable, average, okay, moderate, satisfactory, ordinary 

Step 3: Consider the context of your mentions

Data on most popular hashtags, negative and positive mentions in a specific period via Sprinklr platform

This is where sentiment analysis can get tricky. 

The number of sentiment-related terms in your searches doesn't always tell the whole story of how customers feel. It's important to review mentions carefully and account for potential analytical errors. 

Sarcasm can also throw off sentiment analysis. For example, when someone posts, "I love it when I lose my luggage after a nine-hour flight," they're obviously not thrilled about the experience.  

While sentiment analysis is usually accurate, outliers like these can occur. For the most comprehensive sentiment analysis, it's best to combine manual listening with machine learning techniques. This brings us to our next point.

5 tips to improve your sentiment analysis using a tool 

When it comes to sentiment analysis, accuracy is key. You want to ensure that your analysis captures the true sentiment behind the comments. So, let's explore some valuable tips to enhance your sentiment analysis using powerful tools and techniques. 

  1. Train the tool with relevant data: Provide the sentiment analysis tool with a training dataset that closely matches the type of social media data you will be analyzing. This will help the tool understand the nuances of language, slang and context specific to your target audience. 

  2. Fine-tune the tool: Many sentiment analysis tools allow you to fine-tune their models based on your specific requirements. Use this feature to customize the tool to better understand sentiments related to your industry, brand or specific topics. 

  3. Account for sarcasm and irony: Sarcasm and irony are common on social media and can be challenging for sentiment analysis tools. Consider using techniques like context analysis, lexical analysis or machine learning models that can identify sarcastic or ironic statements more accurately. 

  4. Consider the context: Sentiment analysis results can vary based on the context in which the content is shared. Take into account factors such as the user's profile, previous posts, followers and the overall discussion or conversation surrounding the content. 

  5. Validate with human judgment: While sentiment analysis tools provide a good starting point, it's important to validate the results with human judgment. Create a small sample of manually labeled data to evaluate the tool's performance and make adjustments as necessary. 

If you need any sort of help to set up your social listening topics so you can improve social media sentiment analysis, don’t think twice to contact us — our experts will be more than happy to give you a helping hand. 

3 Ways to use sentiment analysis insights in your marketing strategy

Sentiment analysis is like having a secret weapon for your business strategy. It's used by organizations worldwide to unlock valuable insights and boost their success.  

Let's explore the different ways you can put sentiment insights to work for you: 

Analyze your product

Sentiment analysis can give you the inside scoop on your customers’ opinions and feelings, focusing on specific features like price, quality and packaging. Say you just launched a hot new item and want to know how it's doing in the market.  

With a powerful Unified Customer Experience Management (Unified-CXM) platform, you can gather real-time info using targeted keywords, helping you understand customer sentiment like never before. 

Sprinklr-s sentiment analysis widgets

Keep tabs on social media  

These days, everyone's all about sharing their thoughts on social media. Platforms like X, Instagram and Facebook have become the go-to spots for expressing opinions and feelings. That's where sentiment analysis steps in to save the day.   

You can use enterprise social media tools like Sprinklr to manage multiple social media accounts, catching wind of what people are saying about your products or even industry trends. This lets you analyze heaps of customer feedback, respond to important reviews and nip potential PR crises in the bud.   

Sprinklr-s listening widgets to manage crisis and reputation

Outsmart your competition 

Sentiment analysis isn't just about your own products, it's also a great way to stay ahead of your rivals. By digging deep into market research and understanding your competitors' strategies, you can gain a competitive edge.  

Let's say your rival releases a new product or service. With sentiment analysis, you can find out what consumers love (or hate!) about it and use that intel to improve your own offerings and outshine the competition. 

Sprinklr-s Listening widgets to showcase competitor social performance

How Ferrara Candy sweetens fan engagement with Sprinklr 

Ferrara Candy Company, a beloved name in candy with favorites like Lemonheads and Laffy Taffy, turned its digital presence into a dynamic platform for fan interaction using Sprinklr. 

How: Ferrara implemented Sprinklr in 2019 to revolutionize how they connect with candy fans online. Using Sprinklr's Social Listening, Ferrara can instantly spot and act on social interactions. This was highlighted when singer Halsey requested a custom Trolli flavor and Ferrara quickly responded, resulting in significant social media buzz.   

Another example includes engaging with Columbus Blue Jackets fans by distributing Fun Dip at games after noticing a trend started by team CMO Kathryn Dobbs. These strategic moves, part of Ferrara’s Brand Fan program, have significantly boosted their media presence and deepened fan loyalty. 

The result:   

🎉 Over $2M in earned media value in 2021  

🎉 Over 40+ social media accounts managed 

🎉 Enhanced control and creativity over content across multiple brands  

Ferrara Candy connects with fans to make every sweet snacking moment memorable

Final thoughts  
It's crucial to understand how your followers and customers perceive your brand. Neglecting their feelings would be a big mistake. Luckily, social sentiment analysis eliminates the need for guesswork. By actively monitoring and analyzing social media conversations and beyond, you gain valuable insights into people's thoughts about your business, thus improving your decision-making with the help of data.

Get access to Sprinklr Social's Advanced Plan.

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Related Topics

Sentiment AnalysisSocial Listening: A Complete Guide for MarketersHow to Manage Customer Engagement on Social Media

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