Social Media Monitoring is bit like finding a needle in a haystack, or lots of needles but in a big haystack. For most brands there are dozens or hundreds of interesting mentions every day, but the problem is that they are hidden among thousands of less interesting or completely irrelevant mentions. Defining the query properly, with Boolean words like AND, NOT, OR etc., can reduce this problem so that it feels more like looking for needles in a mere handful of hay (apologies for stretching this metaphor uncomfortably far).
How does sentiment analysis work?
abril 20th, 2011. Publicado por dominickSentiment analysis continues to be one of the most debated areas in social media monitoring, so we thought we’d give a brief overview of the topic and how we approach it at Brandwatch. Here’s our resident expert, Dr Taras Zagibalov, who conducts all our language research and works alongside the tech team to continuously improve our automatic sentiment classification. Over to Taras:
There are two major techniques used in automatic sentiment analysis. The most frequently used one in commercial applications is based on linguistic resources, the other is based on machine learning.
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