Sentiment Analysis Tools enable organizations to analyze all forms of text data to determine the overall sentiment, opinion, or emotional tone expressed by the users in their messages. These tools use technologies such as machine learning, natural language processing (NLP), text analysis, and biometrics for analyzing and breaking a large amount of text data into small chunks to identify the underlying sentiment of a message. The underline sentiment can be positive, negative, or neutral, which is calculated by assigning the sentiment score based on a pre-determined scale to each chunk. These tools also provide multilingual support to enable sentiment analysis across different languages. These tools are commonly used in marketing, customer support, e-commerce, and finance.
"Lexalytics is helping us generate more insights from complex textual sources."
We are using Lexalytics to extract insights and meaningful information from unstructured text data such as social media posts, public surveys, online customer reviews and other textual sources. Lexalytics ability to combine machine learning techniques with natural langauge processing, for effective analysis of textual contents makes it our preferred text analytics platform.
"Transform the customer experience journey with Azure Text Analytics"
Azure Text Analytics has empowered our organization to gain insight from unstructured text data, enabling sentiment analysis, entity extraction, key phrase identification and language specific processing using the natural language processing techniques. It offers a set of powerful APIs that can analyze and understand unstructured texts, including documents, social media posts, user feedback, emails, etc., We have seen a significant improvement in customer experience, automating data processing, and deriving valuable insights for decision making and business intelligence using this tool.
"IBM Watson NLU: Excellent solution for working with customizable entities"
IBM Watson NLU has been instrumental in streamlining our internal processes. We rely on it heavily to analyze large volume of text, enabling us to extract key insights and otimize out operations with efficiency and accuracy.
"The best survey app"
Best app for all kind of surveys, need artificial intelligence for context analisis
"gain deep insights into the world of sentiment media analytics"
Talkwalker has been a delight for my social media team to understand social media conversations. It gives real-time insights into what people are talking about our brand and industry. The reports are also super helpful in showing us the impact of our social media efforts. It's also easy to keep up with the trends and what our competitors are up to.
"Quick go to market, reasonable princing"
Solid tool for brand monitoring. Quite useful for local presence.
"Best Outsourcing"
It has been very helpful having Hitech as our offshore outsourcing partner in India. Hi-tech has made it a lot more efficient for my team to respond to our clients on all social platforms.
"NLP with Rosette"
I had satisfactory experience using Rosette for my text analytics and NLP requirements
"SAS Visual Text Analytics for NLP"
SAS visual text analytics is a an NLP tools for analysing unstructured text data such as customer feedback, new articles, online posts. It uses Machine learning algorithms to extract insights and sentiments or topics for large sets or volume of data