Emotion & Sentiment:
The advent of social media has made expressing opinions an everyday routine. Humans express. There are many kinds of emotions and sentiments involved in every opinion uttered. An emotion may be a display of reaction due to a situation by thought or actual occurrence, whereas a sentiment is a belief that has emerged from the emotions. Expression has become essential, moreover a right and there seems to be no way in stopping opinions from flooding in. An opinion has to be said.
Why has this concept of emotional and sentimental analysis found its way into technology? What has it done?
Let me break it downright simple. Habits, yes our everyday habits, certain of which we find it easy to change but rest are only intermittent and it tends to return with a bang, eg: Smoking. These are all phases of human contemplation. Bases upon our likes and dislikes, reasoning and priorities, we step from one phase of change to another. To all these changes we react emotionally. We attach sentiments to life and objects which inturn drives our behavior toward a certain person or a thing.
What do others think?
You slip over a banana peel, what immediately you think is, NO not getting up or the pain, You look around to see who is watching and what will they think?
Likewise for any business, an important part of the information-gathering behavior has always been to find out what other people think. With the growing accessibility and fame of opinion-rich resources such as online reviews, personal blogs, etc, we seek out and understand the opinions of others.
So, how does this affect business?
Customer engagement is very important to every business and retention is another aspect. Say for example, “I want this waffle so bad “and “the waffle was so bad”. Compare the emotion of these two sentences convey. First sentence has a positive tone and the second has a negative tone. While we are able to differentiate it, codes are written to capture only the first half. That is, when the word “bad” is spotted it automatically segregates it as both the sentences are of negative tone, which is wrong. The whole concept of emotional and sentimental analysis becomes inaccurate at this instance.
Is Good, Bad or Neutral just enough?
Apart from search engines, Social media platforms are pools of raw data. Facebook reached its initial dominance in social market through power of more data rather than algorithm. At the same time, the sheer volume of raw data is also a break through to better make sense of opinions. A proper sentiment analysis that determines the polarity and polarity strength makes more sense. An algorithm which captures the in-depth meaning and feel of the entire sentence will only fetch the best possible outcome. Thereby the derivative from the above analysis will yield the exact true identity of the speech. This will enable us to see the how the audience have reacted toward a particular product or service.
Why it matters?
- Helps make sense from thousands of online intrusions.
- Help detect early warning of how you are performing on social platform
- Helps you find unknown problems.
- Prevents recurrence by knowing what is required at the moment
The in-depth analysis implicates finding opinions in social media content and taking the excerpt of the sentiments they contain.
How can we help you?
Synctag formulates the accuracy of automated tools by the algorithm that governs it. Automated tools with the ability of a human to override its workings will only be the most accurate way. Synctag has come up with the accurate algorithm, dealing with human speech and opinion, so often unpredictable, calls for an extremely complex one.
The content is positive if there are more positive keywords than negative. The content is termed negative if there are more negative keywords. But this analysis does not stop here and there is more to it like detecting rhetorical questions, differentiation from sarcasm like Silence is golden, duct tape is Silver.,etc. The results are proven and amazing.
With sentiment analysis, we delve and analyze “quality metrics”.
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