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Digimind Unveils Digimind AI Sense to Enhance Insights Relevance and User Experience
November 2, 2018 News AI Artificial Intelligence


Digimind, the global leader in social listening and market intelligence, today announced a milestone update to Digimind Social with the launch of Digimind AI Sense as the foundation of AI-powered features, including joint research work from Digimind Labs and IBM Research teams.

The unprecedented amount and complexity of web and social data, coupled with increasing consumer expectations in the age of the Empathy Economy, has created an incumbent need for marketers to turn to artificial intelligence (AI) to deliver better customer experiences. Its ability to analyze large amounts of information with more granular personalization allows marketers to focus their efforts on the human interaction consumers are demanding.

To alleviate these pressing demands, Digimind introduces Digimind AI Sense, a new series of AI-powered features within the Digimind Social platform. By combining the breadth of its 850M sources with advanced machine learning technologies, Digimind Social customers will be able to harness vast amounts of social data with unmatched levels of accuracy, while improving ease to access information.

Digimind AI Sense leverages the hybrid approach of machine learning and Natural Language Processing (NLP), as well as image recognition capabilities, allowing a whole new user experience in Digimind Social:

  • Smart Classification: smart classification is the automated tagging of mentions based on user logic. In the initial tag setup, users will be presented with a limited set of mentions related to this tag, for them to confirm the relevance. Based on the inputs, the combined power of machine learning with NLP is able to understand the pattern of mentions related to the tag, and automatically tag all collected mentions for prompt and relevant data organization.
  • Sentiment Analysis: the machine learning and NLP algorithms for sentiment analysis have been trained on thousands of qualified mentions. This means that no additional user validation is required for sentiment analysis to be relevant, saving precious time, and providing highest levels ever of accuracy on sentiment analysis. Nevertheless, customers will still be available to re-qualify mentions if they have to, and these re-qualifications will be taken into account by the machine learning.
  • Image Recognition: proprietary image recognition algorithms based on deep learning techniques have been trained on thousands of qualified pictures. This allows Digimind Social users to complement textual mentions of their brand with visual mentions of their logo for instance.

Digimind AI Sense’s machine learning and NLP-based features have been developed over the past two years by in-house data scientists from Digimind Labs who worked together with IBM Research teams. Parts of this research work have been publicly unveiled in the paper “Listening Comprehension over Argumentative Content” and will be publicly presented at the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP).

“Over the past two decades, Digimind has consistently focused its efforts on combining sophisticated data processing capabilities recognized by independent research firms, with the most easy-to-use, market-acclaimed user experience. We’re excited to introduce our users to Digimind AI Sense, our new suite of AI-powered features. Not only will it provide more relevant and accurate results, but it will also make the Digimind Social user experience simpler and more powerful than ever before,” said Paul Vivant, CEO of Digimind.