What Is Text Analytics?
Essentially, this term describes the process of garnering meaningful insights from unstructured text data. Through text analytics, we get customer opinions, feedback, and reviews. The data can then be used for sentiment analysis that helps the business make informed decisions.
Here is a list of the top 10 text analytics tools:
- Provalis Research QDA Miner
- Rosette Text Analytics
- Amazon Comprehend
- Microsoft Azure Text Analytics API
1. Discover Text
DiscoverText is a text analysis and data science tool that uses the cloud to analyze large amounts of unstructured free text, survey responses, Twitter data, and more. Users can build adaptive, custom text classifiers using machine learning and crowdsource coding in the semi-structured workflow to find pertinent items and group them into categories like topic or sentiment.
- Using DiscoverText, you can quickly remove duplicates, group-related text, and comments, and auto-highlight any unusual or unpleasant language.
- Create word clouds and delve into them to better comprehend text data graphically and to create tiny subject dictionaries. Create reports in the following formats: PDF, XML, RTF, or CSV for additional analysis.
- To work together on assignments and tasks inside DiscoverText, create peer groups and project networks. You may then share or preserve finished projects online.
- Use Boolean-defined search to find keywords and text, and archive social media posts from both the free and paid Gnip Twitter data streams.
Lexatics provides Semantria, a cloud-based text and sentiment analysis application. This solution is made to assist companies in gathering tweets, SMS, and other comments from customers and then analyzing them to gain extremely important and useful information. The program effectively and elegantly integrates text analytics into the user’s business apps because it is provided as a SaaS.
- Through analysis of tweets, posts, comments, and other documents on social media platforms and elsewhere in the digital sphere in general, it may recognize patterns, identify variations in sentiment, and identify shifts.
- With the help of this program, you may learn things and develop perspectives that can help your business succeed.
3. Provalis Research QDA Miner
Provalis Research QDA Miner Multiple search options are used by an on-premise qualitative data analysis tool to help code and analyze textual data as well as still photos.
- Compared to other qualitative research products on the market, QDA Miner provides greater computer aid for coding, enabling you to code and analyze documents more rapidly and accurately.
- You have unmatched freedom to analyze text and link its content to structured information, including numerical and categorical data, thanks to QDA Miner’s seamless interaction with WordStat, a text mining and content analysis program, and SimStat, a statistical analysis tool.
With the use of MeaningCloud, businesses in the banking, publishing, insurance, and other sectors may extract information from call recordings, surveys, blog entries, and contracts. Managers may use it to automate content publishing processes, create custom reports, and undertake sentiment analysis.
- Data analysts may use voice layout, KPIs, and visualization to get insights into company data using MeaningCloud’s natural language processing (NLP) capabilities.
- In order to categorize texts in accordance with organizational needs, managers can preconfigure parameters and establish new taxonomies using the program.
- Through APIs, MeaningCloud makes it simple to integrate with a variety of other programs, including Dataiku, Google Sheets, Microsoft Word, Zapier, RapidMiner, and more.
5. Rosette Text Analytics
Rosette brings the power of AI to text analysis components within search, business intelligence, e-discovery, social media, financial compliance, and enterprises. Rosette text analytics uses linguistic analysis, statistical modeling, and machine learning to accurately process unstructured text and names, revealing valuable information and actionable data. Basis Technology provides software solutions for text analytics, information retrieval, digital forensics, and identity resolution in over forty languages. The Rosette linguistics platform is a widely used suite of interoperable components that power search, business intelligence, e-discovery, social media monitoring, financial compliance, and other enterprise applications.
- Sentiment Analysis
- Relationship Extraction
- Name Matching
- Name Translation
- Language identification
To do sentiment analysis, subject categorization, intent detection, and entity extraction, small to big businesses may use MonkeyLearn, a cloud-based text analytics platform, to train their own bespoke machine learning (ML) models.
Support teams may use the program to automatically categorize, route, and prioritize request tickets. Customers’ comments and input through reviews, chats, surveys, comments, or support requests can be evaluated by teams to improve the product plan.
- To obtain certain keywords, characteristics, or entities from a text, MonkeyLearn aids developers in creating text extractors.
- Numerous other capabilities are also available, including process automation, historical tracking, tag prediction, classification, data input, and visualization.
- A number of third-party programs, including Zendesk, HelpScout, Google Forms, Airtable, Gmail, and others, are integrated with MonkeyLearn.
- Monthly subscriptions are available for the solution, and phone, email, and live chat assistance are all accessible.
AYLIEN provides Text Analysis & News APIs that allow users to make sense of human-generated content at scale. AYLIEN Text API is a package of Natural Language Processing, Information Retrieval, and Machine Learning tools for extracting meaning and insight from textual and visual content with ease. AYLIEN provides Proper categorization, Concept Extraction, and Automatic Hashtag Suggestion. Concept Extraction takes Entity Extraction to new heights, providing Linked Data for topics mentioned, including semantic types and URIs. Automatic Hashtag Suggestion helps you get more exposure for your content on Social Media.
- Sentiment Analysis
- Entity Extraction
- Concept Extraction
- Language Detection
- Hashtag Suggestion
- Batch Processing
- Image tagging
Data analysts may create new data mining methods, set up predictive analysis, and more with the help of the range of technologies offered by RapidMiner. RapidMiner Studio, RapidMiner Server, RapidMiner Radoop, and RapidMiner Streams are among the available offerings. Designing analytic procedures in the RapidMiner Studio uses a drag-and-drop graphical interface. You can include your existing, customized algorithms using the open APIs. You can do more than 1500 operations using The Studio’s template library, batch processing, several data visualizations, and automated charting on all significant platforms, sources, and systems.
- Brand-new templates, such as those for direct marketing, sentiment analysis, and churn reduction
- Runs on every central operating system and platform
- Perform over 1500 operations. From attribute creation through market-based analysis to data splitting.
- Various data handling techniques
9. Amazon Comprehend
A natural language processing tool called Amazon Comprehend can draw conclusions from text and interpret them. In order to extract text from documents, support tickets, reviews, emails, and social media feeds and categorize that material based on keywords, sentiment, entities, and other factors, Amazon Comprehend uses built-in OCR and NLP capabilities.
- To grasp the sentiment concealed in the text, Amazon Comprehend identifies the language of the text and extracts crucial details like locations, occasions, or persons.
- This program analyzes text using parts of speech and automatically groups collections of text files according to subjects or phrases.
- Utilizing Amazon Comprehend, businesses may create text categorization models or entities specifically suited to their brand’s requirements.
- This software allows organizations to send personalized information to their consumers using text file subjects. They can also improve customer search and navigation to boost customer retention.
- Organizations may also expand the capabilities of this NLP software to find certain phrases and categorize documents according to their operating culture.
10. Microsoft Azure Text Analytics API
Microsoft Azure Cognitive Service Text Analytics API detects sentiment, key phrases, topics, and language from your text. For Sentiment Analysis, the API returns a numeric score between 0 and 1. Scores close to 1 indicate positive sentiment and scores close to 0 indicate negative sentiment. The sentiment score is generated using classification techniques. The input features of the classifier include n-grams, features generated from part-of-speech tags, and word embeddings. English, French, Spanish and Portuguese texts are supported. For Key phrase extraction, the API returns a list of strings denoting the key talking points in the input text.
- Sentiment analysis
- Key phrase extraction
- Language detection