WE OFFER FREE SOCIAL MEDIA SENTIMENT ANALYSIS TOOLS. Know what consumers are saying about your brand on social media, such as Facebook and Twitter. It entails sentiment analysis, positive / negative sentiment score, 100% All-Natural Language Processing (NLP) engine without the use of dictionaries. Some studies suggest that language processing tools are better at determining sentiment than our intuition.
Social media sentiment analysis tools are used by companies to track, analyze and interpret customer conversations on social media. You’ll find the most comprehensive list of free social media sentiment analysis tools in this article from Buffer.
Keyhole is a tool for agencies and enterprises covering campaign monitoring, influencer marketing, brand monitoring, event monitoring, and market research. Part of this wide range of features includes sentiment analysis. It appears on the Dashboard of your Hashtag & Keyword Tracker. It calculates a sentiment score based on positive and negative posts: Sentiment Score = Positive / (Positive + Negative).
You can filter by sentiment (using a five-point scale of emoji) in the Posts tab. You can also edit that level of sentiment if you believe it necessary. For example, Keyhole acknowledges that its Machine Learning algorithm for Sentiment is still learning to detect sarcasm and industry-specific sentiment.
Social Searcher monitors keywords, hashtags, and usernames across all social media platforms. You’ll receive a bunch of social analytics, including audience insights, popular hashtags, and social influencers.
The free version includes a sentiment analysis tool, which provides the overall sentiment of social media data on each platform and a breakdown of popular posts that have been categorized as negative and positive.
Mention offers real-time monitoring, along with competitive analysis, social media management, custom insights, and automated reports. In addition, it can be helpful for damage control, so you discover simmers of discontent before they become raging fires.
Although sentiment analysis isn’t available in the lower-level Free and Solo plans, Mention does include it in the three higher tiers. It identifies positive and negative mentions of your brand and competitors around the web. Sentiment analysis is one of Mention’s advanced filters, along with influence, source, and more. You can use sentiment analysis to identify who’s talking negatively about you so that you can control the damage. Conversely, you can use social media sentiment analysis to find people saying nice things about you, share their comments, thank them, and spread the good word.
Social Mention is a social media search and analysis platform that aggregates user-generated content into a single stream of information. You can easily track and measure what people say about you, your company, a new product, or any topic across the web’s social media landscape in real-time. Social Mention monitors 100+ social media properties directly, including Twitter, Facebook, FriendFeed, YouTube, Digg, and Google.
It focuses on four crucial factors:
- Strength – the likelihood that your brand is being discussed on social media
- Sentiment – the ratio of mentions that are generally positive to those that are predominantly negative
- Passion – a measure of the likelihood that individuals talking about your brand will do so repeatedly
- Reach – a measure of the range of influence
Best for: audience analysis, market research, reputation management, competitor analysis.
Awario is a web-based social listening tool, with sentiment analysis being only a part of its vast capabilities. The data Awario analyzes comes from social media platforms (including tweets, posts, Reddit threads, etc.), forums, blogs, and websites, and you get access to sentiment analysis as soon as you log into the tool. It can estimate sentiment of the mentions in real time.
You set Awario to gather online data by putting in the keywords you want to monitor. They can relate to your brand, your product, competitors, industry, or any other phenomena you want to research online.
In the screenshot above you can see Awario’s sentiment analysis of the two major American parties. The tool analyzes the percent of negative sentiment, neutral, and positive sentiment.
Awario does all sorts of real-time social listening and data analytics: it displays the volume and reach of mentions for your keywords, the words commonly used along with them, and breakdowns of the volume of keywords by language, source, location, and more. You can also compare this data, including sentiment, for several groups of keywords. For example, you can find out how much negative sentiment you get online and benchmark the number against your competitors.
All this information is depicted through comprehensive drafts and can be exported and easily shared with your coworkers.
You can try this software for free for seven days.
There are three main plans for users: Starter is $29, Pro is $89 and Enterprise is $299 a month. The prices for yearly plans start at $290. You can also choose a Custom plan should you need more powerful analytics.
Best for: brand and campaign monitoring, competitor analysis, reputation management.
Talkwalker is another sentiment analysis tool that analyzes social media data. It uses its AI to check and analyze the tone of individual online mentions collected from major social media networks as well as blogs and forums. It can even automatically detect basic forms of sarcasm.
The tool allows you to track customer trends and see which features of your product your customers are drawn to, and which features turn them away. Similarly to Awario, it offers some competitor intelligence capabilities along with other important online data metrics such as engagement and demographics.
You can get a free demo if you want to see Talkwalker in action. The prices start at $9,600 a year.
Best for: market research on Twitter.
In case you’re looking for a specific tool that analyzes sentiment on Twitter, here’s the best one.
Twitter can be an amazing platform for research, especially in tech, media, politics, and some other industries. Unlike other tools on this list, the app arranges the data on a spectrum of emotions organized along two axes: unpleasant to pleasant and active to subdued. The data is also analyzed by major topics featured in conversations around your keywords to help you understand the deeper meaning behind the tweets.
The application is free.
You can use MonkeyLearn to train custom machine learning models to get topic, sentiment, intent, keywords, and more. It has tools that target support teams, product and CX teams, and developers. MonkeyLearn offers models that you can use to analyze your text. Models can be used for categorizing text or extracting pieces of information, and you can combine them for complex processes. Sentiment analysis is one of the models.
There is a general Sentiment Analysis model that classifies texts in English. You can use it for all kinds of text.
MonkeyLearn has created a series of specialist sentiment modules, however. For example, the Tweet Sentiment module classifies tweets in English according to their positive, neutral, or negative sentiment. Similarly, you can use the Product Sentiment module to classify product reviews and opinions in English as positive or negative according to their sentiment. Other specialist sentiment modules include Hotel Sentiment, Restaurant Sentiment, Movies Sentiment, and Airline Sentiment.
You can use Repustate to find insights in your surveys, social media, videos, podcasts, text documents, news, and product reviews. Their AI-powered API automates the manual task of extracting insights from unstructured data using semantic technology, helping you improve workflow and efficiency. You can use these insights to deeply understand the feelings and motivations of your customers.
You can also use Repustate internally to measure the perception of your organization and employee engagement, using their language analysis technology, and improve top talent retention, acquisition, and overall productivity. Their Sentiment Analysis API highlights emotion and intention hidden in language and data, providing tangible results and actionable insights.
Best for: customer support, customer feedback analysis.
Clarabridge is a tool that helps you analyze communication with your customers including emails, chat conversations, and surveys. It uses grammatical and lexical principles combined with machine learning to analyze each sentence in the text individually and the sentiment of the text on the whole for a multitude of languages. Additionally, it is able to dissect audio data which can be useful for call centers.
Since the tool primarily acts as a Customer Experience management software, it provides a bunch of features to improve your communication with customers. For example, Clarabridge differentiates between urgent and non-urgent requests and notifies you about the former.
A free demo is available. The price is available on request.
Best for: data research.
Lexalytics is another text analysis tool that can be used for all kinds of business purposes. It sources data from surveys, social media comments, reviews, and so on and uses natural language processing to identify whether a piece of text is negative, positive, or neutral. The tool can be integrated with other software through its Cloud API or you can get it as an add-on for your Excel sheets. The tool is fully customizable, although you’ll need some basic data analysis skills to add your customizations.
The tool offers free demos. The pricing is revealed upon request.
Meaning Cloud offers multilingual text analytics – from news headlines and social media to video subtitles and call transcriptions. One of its tools carries out sentiment analysis. Automatic sentiment analysis allows you to process high volumes of data with minimum delay, high accuracy and consistency, and low cost, which complements human analysis.
Their Sentiment Analysis API performs detailed, multilingual sentiment analysis on information from different sources. It analyzes selected text to determine if it expresses a positive, neutral, or negative sentiment (or if it is impossible to detect). It identifies individual phrases and evaluates the relationship between them. This results in a global polarity value of the text as a whole.
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