Social Listening Deoptimization

During one of my classes, Niña Terol, social media manager of Bam Aquino and Kiko Pangilinan, mentioned that they use Radian6 to monitor online sentiments for her employers.

Social Listening in the Philippines
I realized that, much like with how people found a away to exploit *ahem*, I mean optimize search engine presence and relevance. The same could be done for social listening. For example, let's make a placeholder paragraph:
Senator Bam Aquino is so annoying. He is so negative. I disagree with his policies. He shouldn't be in the next election in the Philippines.
As you can see above, I used several keywords that I assume they input in their social listening tools to find information about their employer: "Senator Bam Aquino"; "policies"; "election"; "Philippines".

Although these are assumption keywords they search for, I'm betting they're pretty close. At the same time I added the following to fool Radian6 and denote negative sentiment by using keywords such as "annoying"; "negative"; "disagree".

Like I said, much like with search engine optimization, the same are potentialities in the industries of social listening: there will be white hat and there will be black hat.

Brands can hire content farmers to farm false negative sentiments to throw off competition. They could also falsify positive sentiments to drive the marketing and sales of their competitors elsewhere. I believe this will be a trend and new industries will be emerging or at least new branches will grow from the current SEO industries.

While social listening is at a very young age, I believe it to be very vulnerable to spam and black hat attacks. Once these industries emerge, the social listening industry's credibility as a marketing tool will be put in question.

Just my random two cents.

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