Discovering brand impact: Sifting through all the noise of chatter to find insights that are actionable

This paper presents a new text analytics tool designed to help analyse big data and gain insights into customer opinions from unstructured data such as social media chatter.

Discovering brand impact: Sifting through all the noise of chatter to find insights that are actionable

Henry Cheang and Stephen PatonPotentiate and AGL Energy

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Introduction

The world creates 2.5 quintillion bytes of data per day from unstructured data sources like consumer complaints and feedback, text, messages, email and documents, survey and social media posts (IBM, 2012). Gartner defines unstructured data as content that does not conform to a specific, pre-defined data model. It tends to be the human-generated and people-oriented content that does not fit neatly into database tables (Gartner,...

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