On January 15, 2016

Sentiment analysis in Social Media. What is it and how is it measured?

The importance of measuring sentiment in Social Media

In the beginning of social media analytics, it was attributed much importance to quantitative data. But increasingly, them are combined with the importance of qualitative analysis and focused on the sentiment generated by the users.

It’s a natural evolution at company level, because in the beginning of the presence in social media networks, the focus is on interact with the users. But as they mature their social profiles, it is increasingly the importance of the positive attitude, reactions and responses of customers to the brand.

For social media networks user is important that companies listen their opinion, because they are doing an effort to give it, and it is not in vain. In addition, his words say more than a “Like” or “Share”. By analyzing this information, companies can know better their customers, and know what they are really thinking about the company. Get words like satisfaction, trust, deception, passivity … In general, the feeling of users is difficult to quantify. On the other hand, if users see that companies attach importance to your comments, they will be more motivated to give their opinion.

How is sentiment measured?

In Social Media analytics, the sentiment data is used to know the community’s climate in relation to the brand. Although, it really is a difficult metric to measure because the tool must analyse whether a comment is positive, negative or neutral. Depending on the type of comment that must be analysed, this may be easier or more difficult. This analysis is performed under the literal semantics of words, thing that is complicated for languages as the Spanish, in which irony and humour are present in much of the opinions that users provide in social profiles.

A satisfied community, is not only one that has positive feelings toward the brand. Also it is which after making a criticism or claim, is able to rebuild comments with positive feeling. Thus, analysing the sense of community, a company can work on turning the negative sense of certain users, in positively sense. This kind of users care in social media networks, is one of the qualities of Lovemarks, which care about the satisfaction of their customers, they value it and always be willing to prescribe them.

The sentiment analysis by SOMA

SOMAOne of the features that has developed in the Smart Social Media Center SOMA, is the ability to measure the feeling of user interactions with the profiles that are being analyzed.

This tool has the ability to provide an accurate analysis result using emotional ontology approach.
To do this, it has developed an algorithm able to analyse and interpret the emotional significance of the comments made by users.

But not only that, to overcome the barrier of misunderstanding, SOMA algorithm can be trained by people who are using it. Analyzing the toughest comments manually, and telling to the algorithm how categorizing it. The algorithm in each training will learn about these interpretations of comments and apply their knowledge in future occasions.

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