Posts Tagged: NLP

3 Best Practices for Coding Open-Ended Questions

Open-ended survey questions often provide the most useful insights, but if you are dealing with hundreds or thousands of answers, summarising them will give you the biggest headache. The answer lies in coding open-ended questions. This means assigning one or more categories (also called codes) to each response. But how to go about it?

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Actionable insights: can data analysis software deliver them?

When it comes to making sense of data, getting actionable insights is the holy grail. But what does this even mean? When is a finding an insight? When is an insight actionable? Can data analysis deliver them? Let’s get to the bottom of this by looking at some examples. Imagine, you have conducted a survey of 100,000 students, and you seek actionable insights for what to improve at a university. Non-insightful vs. Insightful Knowledge Non-insightful…

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Top 3 reasons why most NLP fails

Understanding customer comments, on a large scale, needs to be automated. So, it requires Natural Language Processing (NLP) or Text Analytics. Unfortunately, most open-source NLP tools were developed on text researchers have easy access to. These are typically news articles, research papers and movie reviews. I learned that the analysis of customer comments is quite different, and here is why.

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Key take-aways from sentiment analysis symposium 2016

In July 2016, I was fortunate enough to speak at the Sentiment Analysis Symposium in New York. It is one of the most important events for those who invent text analytics solutions and for those who use them. I also attended the co-located sentiment analysis tutorial run by Jason Baldridge. Overall, this was an excellent event to get up to speed on the current state of affairs and the future outlook. So, here are my…

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Customer Experience Update