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Top 5 Open Source Sentiment Analysis Tools in 2024

Hey there! Ever wondered about diving into sentiment analysis for your business but got scared off by the jargon? Well, worry no more! We’ve got your back with this article, where we’ll introduce you to some cool open source and no-code sentiment analysis tools. And the best part? You can give them a spin without breaking the bank!

Picture this: the text analytics market is set to hit a whopping US$ 4.84 billion by 2026! And guess what’s stealing the spotlight? Sentiment analysis! It’s become a global sensation in the text analytics realm.

If you haven’t hopped on the sentiment analysis bandwagon yet, don’t fret! We’re here to help you discover the top tools and real-world examples. Get ready to unlock the potential of this tech without burning a hole in your pocket!

Table of contents

How open source platforms are used for sentiment analysis?

Exploring the world of sentiment analysis? Awesome! Let’s break down how open source platforms play a crucial role in this process.

In our comprehensive sentiment analysis guide, we outlined three key steps: data acquisition, model selection, and analysis. Now, open source platforms mainly shine in the third step – the analysis part. Here’s the scoop: these platforms come armed with a text classifier. This nifty tool goes through your text, tagging words or groups of words as negative, positive, or neutral. Plus, it dishes out an overall sentiment score for the entire text.

Think of sentiment analysis frameworks as the cool cousins of natural language processing (NLP). They share similar concerns but focus specifically on deciphering sentiments. When you’re exploring open source solutions, keep a keen eye on a few key factors: accuracy, multilingual performance, and the platform’s ability to seamlessly connect with your data source. The magic really happens when these solutions are actively supported, ensuring top-notch accuracy and reliability. Ready to dive into the sentiment analysis adventure? Let those open source platforms do the heavy lifting for you!

Top open-source sentiment analysis coding packages

spaCy

Stars on GitHub: 22.5k ⭐

spaCy rules the sentiment analysis kingdom on GitHub, boasting a whopping 22.5k stars in the Natural Language Processing arena. It’s a versatile powerhouse, supporting over 60 languages and flaunting some seriously comprehensive documentation. Built primarily in Python, spaCy is a fusion of six different programming languages, making it a robust choice. Whether you’re a newbie or a coding maestro, spaCy’s extensive community content has got your back, offering assistance across all skill levels.

NLP.JS

Stars on GitHub (2024): 4.8k ⭐

If you’re a JavaScript enthusiast, meet NLP.js – a sentiment analysis package that’s making waves with 4.8k stars on GitHub (as of 2024). Developed by the Axa Insurance Group, this open-source gem is a go-to for JavaScript developers. With JavaScript being the go-to language for web scraping, NLP.js is tailor-made for those just starting out in sentiment analysis. Dive into its extensive documentation and examples, perfect for beginners. Not to mention, it flexes its multilingual muscles by supporting a cool 40 languages right out of the box.

Pattern

Stars on GitHub (2024): 8.2k ⭐

With a solid 8.2k stars (as of 2024) on GitHub, Pattern is standing tall in the sentiment analysis realm. Primarily built in Python, this package offers a unique twist compared to spaCy. Here’s the scoop: Pattern not only dives into sentiment analysis but also brings data collection to the table. You can scoop up data through web scrapers or integrate APIs seamlessly. It’s like a sentiment analysis party with a side of comprehensive data solutions!

Top low-code or no-code open-source sentiment analysis tools

MeaningCloud - Used by Big Corporations

MeaningCloud isn’t just a player; it’s the MVP for sentiment analysis, trusted by major corporations. What sets it apart? Well, it generously offers a free tier that might just align with your sentiment analysis needs. But here’s the game-changer – this free tier supports API integration, adding a dose of automation to your text analysis. Unlike many other paid tools offering just trial periods, MeaningCloud keeps the free service flowing continuously. Sure, it has some volume and capability limits, but hey, it might just be the perfect fit for your business without costing a dime.

Social Searcher - Social Media Sentiment Analysis Specialist

Social Searcher steps into the ring with a specialization in social media sentiment analysis. Picture this: big corporations have trusted its prowess. What makes it a knockout? The dashboard view! It’s your secret weapon for comparing platforms and gaining a crystal-clear understanding of the big picture for a specific keyword. Imagine the marketing possibilities! Need real-time searches? Social Searcher’s got you covered for free. And if you crave that extra punch, their paid plan, starting at a reasonable rate in 2022, unlocks even more dashboard magic.

Let's break down the pros and cons of open source sentiment analysis platforms

Pros

Cost-Effective: Open source platforms are often free or available at minimal cost, making them an attractive option, particularly for companies with in-house developer teams.

Quick Implementation: Swift deployment allows businesses to swiftly try out or pilot sentiment analysis for specific use cases, providing a fast route to assess the technology’s value.

Innovation and Community Support: Open source platforms thrive on innovation and continually evolve with the help of online communities. This collaborative environment often leads to the introduction of new features and improvements.

Cons

Security Compliance Risk: Especially concerning for large corporations, there is a risk of non-compliance with stringent security requirements. Open source platforms may lack the robust security measures needed for handling sensitive corporate data.

Limited Support: The absence of a formal support layer may result in limited assistance for specific troubleshooting needs. Companies relying on open source solutions may face challenges in obtaining dedicated support.

Sustainability Concerns: Open source platforms may face sustainability issues due to factors such as solution discontinuity, version upgrades, or changes in licences and fees. This instability can pose challenges for businesses relying on these platforms in the long term.

Dependency on Separate Data Processing: Open source sentiment analysis platforms are often dependent on data being collected and processed separately. This adds complexity to the overall workflow, potentially requiring additional resources for data handling.

In weighing the pros and cons, businesses should carefully consider their specific needs, security requirements, and long-term sustainability goals before opting for open source sentiment analysis solutions.