[Free Download] The Practical Guide: For Applying Effective Machine Learning to Social Listening Analysis

If you analyze social data, it’s likely that you have a healthy skepticism towards machine learning – or maybe that’s just me?!

As a practitioner, I have to confess that I would rather control the segmentation of my data myself. My experience of using auto artificial intelligence (AI) functionality in social listening tools is that they never segment and code the data in a way that is meaningful for the questions that I’m trying to answer – it’s all been a bit of a waste of time.

So, when the team at Converseon.AI got in touch about their latest whitepaper ‘The Practical Guide: For Applying Effective Machine Learning to Social Listening Analysis’ I was a little apprehensive about what I would find and that I’d be baffled by the technical aspects. Turns out that I had nothing to worry about and actually learned a thing or two.

The biggest thing that I’ve taken away is that “every model will contain errors and yours is no exception”. That’s a big take away as we’re always given the impression (or it’s implied by vendors) that the AI will produce the insights we’ve been looking for. That’s never been the case for me and the depth of analysis I want to take. Key things you’ll learn include:

● How machine learning is transforming the analysis of insight-rich language data.
● The difference between general machine learning models and “intelligent” models (and why this matters).
● Steps to evaluate and improve model performance.
● How auto MLaaS is enabling general analysts to build, validate and deploy sophisticated models.

There has been a lot of marketing talk about machine learning and AI but we’ve always lacked a practical approach to do it right, this eBook provides the starting point. If you’re a social analyst or social media researcher and maybe aren’t the ones applying the process this eBook will give you more awareness of what happens and where you can probe for better questions.

The lesson for practitioners is that we still have an important role to play in the segmentation process, we should be able to specify the right meaningful segments for our work and the machine can do the heavy lifting through the data. The lesson for vendors selling AI capabilities in social listening. Don’t suggest that the model will be perfect, or you’ll get the right insights at the click of a button – there’s still human analytical work to be done!

Get a free copy of The Practical Guide: For Applying Effective Machine Learning to Social Listening Analysis by clicking this link.

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