This blog post also appears on LinkedIn.
For years – clients have been calling us about social analytics and for years their excitement had been rooted in a particular type of analysis: sentiment analysis.
The promise was that social sentiment analysis could give organizations real time insight into how people felt about a particular marketing campaign, a brand in general, or the customer service they had received. The standard sentiment analysis tools allowed for organizations to see whether social posts were considered to be positive, negative or neutral and more complex tools broke up sentiment into passion and emotion. Additional complexities were addressed – like parsing out phrases within a single post to determine whether one subject of the post was positive while another was negative, without the post being tagged as a resultant neutral.
But some of the largest organizations in the world, working off of some of the most renowned social analytics tools, seem to have soured on social sentiment analysis.
According to these organizations, largely represented by their market insights teams, they discourage their employees and their executives use of sentiment analysis as a definitive measure of success or failure. They say that despite having used multiple tools over the years – and I’m talking the tools which are largely considered to be the leaders in the social analytics space – they have never found sentiment analysis to be particularly accurate.
Perhaps it’s the fault of these vendor’s NLP algorithms, perhaps it’s the simple truth that even people won’t agree on the sentiment of a social media post 100% of the time. It could be western society’s penchant for sarcasm, it could be that there are too many industry specific terms that no vendor could have so many taxonomies for. Maybe our sampling of social data is too biased! Is it our problem for interpreting it wrong or expecting it to work on it’s own without any context? The fact of the matter is that this area has been a massive disappointment to clients and reference customers alike.
If you’re reading this thinking, “well no, it worked for me…” I would love to hear from you in the comments or at my email address email@example.com if you need to keep your comments off the record.
Similarly, let me know if you haven’t seen success here and what you think the drivers behind that problem are.
Looking forward to hearing from you!
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