Sentiment analysis is big business. And it’s only set to grow, with the market projected to hit USD 4.5 billion by 2033—mainly driven by the mushrooming volume of digital content generated daily.
In theory, sentiment analysis software provides PR professionals with insights into how the public perceives the brands, organizations, and individuals they represent. Social media platforms like Facebook, LinkedIn, and Reddit are filled with customer opinions and conversations—data that enables PR teams to better understand perceptions.
However, while sentiment analysis tools can help brands better navigate their reputation management and marketing strategies, most available software platforms fail to deliver on their promises. Vague responses and inaccurate data leave many PR pros with more questions than answers.
In this article, we examine these challenges in more detail and explore how future technologies may address the limitations of today’s tools.
What Is Sentiment Analysis?
Sentiment analysis (or “opinion mining”) refers to the process of identifying, extracting, and quantifying the emotional tone and subjective information within text data related to a brand, organization, person, or topic.
Today’s sentiment analysis tools use natural language processing (NLP), machine learning (ML), and artificial intelligence (AI) to interpret opinions, emotions, and customer feedback.
In its most basic form, sentiment analysis tools evaluate text to determine when someone mentions an organization, person, or target keyword and whether it carries a positive, negative, or neutral connotation.
While traditional media monitoring might tell you that your brand was mentioned 500 times last week, sentiment analysis algorithms reveal whether those mentions were predominantly favorable or unfavorable.
Sentiment data can be gathered from various sources, including social media platforms (via social media monitoring), online reviews, customer reviews on e-commerce sites, online forums (such as Reddit), and survey responses.
Many modern media monitoring tools, such as Hootsuite, Sprout Social, Meltwater, and Cision, incorporate sentiment analysis as a feature. These tools enable PR teams to track mentions and gain actionable insights into the emotional context behind them. These platforms often assign a sentiment score to each mention, quantifying the emotional tone on a numerical scale for easier analysis.
.jpg?width=1400&height=700&name=DTS_Currency_Fanette_Guilloud_Photos_ID6048%20(1).jpg)
How PR Pros Use Sentiment Analysis Tools
In 2025, PR professionals use sentiment analysis tools in the following ways:
1. Brand reputation management: Real-time monitoring enables PR teams to track an organization’s reputation over time, identify potential issues before they escalate, and measure the impact of PR activities on overall brand sentiment.
“Having your messaging appear across multiple places is good for a brand, but it's only impactful if it lands in the way you intend it to,” says Head of Strategy & Insights at Codeword, Jordan Leschinsky. “Sentiment analysis is a helpful way to gauge the positioning and resonance of a brand’s messaging across earned channels and community conversations,” she continues.
“Understanding sentiment helps us decide what areas need to be prioritized for marketing and PR and what impact we need to have for them to be successful.”
2. Crisis prevention and management: By detecting negative sentiment patterns early, PR teams can identify potential crises before they gain momentum and escalate. Real-time alerts for negative sentiment allow these professionals to respond promptly to emerging issues.
3. Campaign effectiveness measurement: By tracking sentiment before, during, and after campaign launches, PR teams can assess whether communications strategies resonate with target audiences. This helps them determine which messages are effective and which need refinement, helping them to pivot and deliver more successful campaigns.
4. Competitive intelligence: When sentiment analysis reveals that competitors’ customers are dissatisfied with products or services, PR teams can highlight their organization’s strengths or adjust messaging to address unmet market needs. This insight can provide a competitive edge, allowing brands to position themselves more effectively in the market.
5. Market research and trend analysis: Sentiment analysis can be used to understand how people feel about specific topics or emerging industry trends, providing valuable context for future campaigns.
6. Fast customer feedback analysis: Rather than waiting for formal feedback channels, sentiment analysis allows PR teams to capture customer opinions in real-time. Popular sentiment analysis tools include Lexalytics, Sprinklr, Mentionlytics, Keyhole, Talkwalker, and Brandwatch.
Machine-Enhanced Sentiment Analysis
Over the past few years, AI, machine learning (ML), and deep learning have significantly simplified sentiment analysis.
Instead of manually reviewing thousands of social media posts and reviews, for example, many PR teams now use AI-powered tools that automatically scan, categorize and interpret public opinion in real-time. These tools rely heavily on natural language processing (NLP) to analyze text data and extract meaningful insights. By leveraging NLP, these tools can better understand the structure and meaning of human language, enabling more accurate sentiment classification.
While ML models typically classify text as “positive,” “negative,” or “neutral,” deep learning models can recognize subtler cues, such as sarcasm or context. The ability to identify neutral sentiment is particularly valuable, as it helps PR teams understand when public opinion is neither strongly positive nor negative, providing a more balanced view of customer feedback. Additionally, advanced tools now calculate a sentiment score for each piece of text, offering a precise numerical representation of the emotional tone, which is especially useful for tracking trends over time.
Challenges in Sentiment Analysis
Unfortunately, many of the tools currently available fail to accurately interpret sentiment, leaving PR teams with their hands in their hair.
“l only do manual sentiment analysis,” writes PR professional Tieja MacLaughlin in a Reddit thread on the topic. “The variance between manual and automated is far beyond a reasonable margin of error.”
“I only report on sentiment if the client has the budget for human analysis,” another Reddit forum member notes in the same thread. “The automated and AI-driven sentiment done by social listening tools is absolute garbage.”
When you discuss these tools with PR professionals, they highlight the following challenges:
1. Limitations in multilingual sentiment analysis: The available sentiment analysis tools are typically trained on English-language data. When they encounter feedback in other languages, they often misinterpret or overlook cultural nuances, idioms, and context-specific expressions.2. Lack of contextual understanding: The software often struggles to grasp the true meaning of words and phrases without considering their surrounding context.
“While these tools provide quick insights, they come with limitations — particularly when human context is missing,” notes Brandi Sims, Founder of Brandinc PR, in a conversation with PR.co.
Take the recent Shedeur Sanders NFL draft situation as an example, Brandi says. Shedeur Sanders, once considered a top quarterback prospect, unexpectedly slid to the fifth round of the 2025 NFL Draft, where he was selected by the Cleveland Browns. His fall was attributed to concerns about his leadership style, pre-draft decisions (like skipping key events and interviews), and the perception of distractions tied to his high-profile father, Deion Sanders.
“There was a flood of commentary about his slide in the draft rankings. If I relied strictly on sentiment analysis, I’d likely interpret much of it as a negative opinion.
“But in reality, the conversation was more nuanced. While people were discussing a negative situation, many comments were sympathetic or supportive of Sanders himself. The overall sentiment wasn’t purely negative toward him.
“This is exactly why human interpretation is essential. It allows for a deeper understanding of context and intent, something sentiment tools alone can easily miss. In many cases, human input in media analysis is far more effective than relying solely on automated sentiment data.”
3. High costs: Implementing accurate sentiment analysis solutions often requires a significant investment. Tools with advanced features, higher accuracy, and the ability to mine vast amounts of data are typically expensive.
Determining the software's costs can also be challenging, as AgoraPulse’s Erica Pollock discovered.
4. Surface-level insights: Sentiment analysis tools can certainly help PR professionals get a quick sense of public perceptions, especially when sentiment is weighted heavily in one direction. However, they often fail to provide deeper insights into neutral sentiment, which can be just as important as positive or negative sentiment. Neutral sentiment often reflects a lack of strong opinion, which can indicate areas where brands need to engage more effectively or clarify their messaging.
“While our team uses these tools to build efficiencies and help us make decisions fast, true understanding of sentiment requires marketers and strategists to get in the weeds of what’s being shared and said online,” Jordan says.
She adds that this deep knowledge level can be a competitive advantage, as competing brands all use the same sentiment analysis platforms.
Where Sentiment Analysis Software Is Headed
The next wave of tools will delve deeper, identifying subtle differences—such as slightly positive sentiment versus strongly positive sentiment—and detecting specific emotions like happiness, anger, or surprise.
Another major shift, according to research published in the Artificial Intelligence Review, is a move toward analyzing not just text but also images, audio, and video. Imagine being able to gauge the reaction to a brand video review based on facial expressions, not just written comments.
Context is also becoming a significant focus. The next generation of tools will be significantly better at understanding the meaning behind words, including sarcasm, irony, and cultural references that often elude today’s systems.
As more brands go global, there’s also a push to make sentiment analysis work across multiple languages and cultures. New tools are being designed to handle slang, emojis, and informal language and analyze sentiment in languages that haven’t been well-supported in the past.
Finally, as these tools become increasingly powerful, there’s a growing emphasis on using them responsibly. The best sentiment analysis platforms of the future are transparent about their workings, helping PR teams avoid unintended consequences.
A Broader Lens: Complementing Sentiment Analysis with Additional Metrics
To truly understand your brand’s media performance, sentiment analysis is just one piece of the puzzle. By integrating other metrics, you can gain a clearer and more actionable perspective. Metrics like domain authority and page authority assess the trustworthiness of the outlets sharing your stories, while share of voice shows how much space your brand occupies in the larger conversation. Engagement levels and content virality measure how well your message connects and spreads, while audience retention can reveal how deeply your audience engages with your content over time. When combined, these insights provide a more complete view of your media impact and help refine your strategies for even greater success.
New PR.co Monitoring Feature Coming Your Way
Sentiment analysis is a field that certainly excites the PR.co team, and we’re constantly innovating to help PR teams demonstrate the value of their work within their organizations.
Right now, we’re enhancing our PR analytics capabilities and developing an exciting new media monitoring feature, which will also streamline sentiment analysis. Stay tuned!
