Growing Importance of Sentiment Analysis In Social Media Analysis

Going by the Oxford dictionary, sentiment analysis can be defined as the process of categorizing opinions those are expressed in a text piece. This process is mainly executed to determine effectively the attitude of the writer on a particular topic whether it is positive, negative or neutral. In case of social media, the opinion of the writer is understood with the help of a post. As the title suggests, let us understand the importance of sentiment analysis in social media.

Growing Importance of Sentiment Analysis In Social Media Analysis

Conducting a sentiment analysis on social media is a great way to find out information and get insights that will further help in:

  • Framing better market strategies
  • Improving the success percentage of a campaign
  • Improving scope of product messaging
  • Developing better customer service processes
  • Implementing lead generation approaches

The above mentioned pointers help in concluding that a watertight sentiment analysis of social media will improve the overall conditions. Care needs to be taken that the sentiment analysis data is accurate so that the right decisions can be taken based on the data results. The popular vendors providing social media analysis confirm that the data analysis is just about 50% to 60% accurate.

Given the emphasis on accurate data, a 50% to 60% accuracy will obviously not suffice. So, this seems like a problem but definitely with a suitable alternative. The obvious solution is to hunt for a better sentiment analysis algorithm.

The entire sentiment analysis process of social media is highly complex and it is mostly a field study rather than being just a feature in a social media tool. Nobody loves complex processes and it is important to simplify these processes in order to obtain the accurate data easily.

Wondering why analyzing the sentiment quotient in social media seems to be such a difficult and complex task? Well, that is primarily because there is scope for viewers to misinterpret the conversation. That’s not all, there is the use of jargons and sarcasm that makes the interpretation tougher. There is obviously the need to simplify the processes and let us check out the different factors that will help.

  • Manual Processing – Human interpretation of the social media posts is considered to be the most rational sentiment judgment analysis. However, human interpretation is individualistic and, thus, it cannot be considered as 100% accurate. Vendors still use this approach along with the help from other tools because of the overwhelming growth social media is enjoying. Seth Grimes believes that social is one of the fastest growing sources of analytical data.

  • Keyword Processing – Keyword processing algorithms bring with it a certain degree of positivity or negativity towards a particular word. After this, the algorithm comes up with an overall score percentage of the entire post. Implementation of this method is fast and predictable; it is also very cost-effective and easy to run. On the downside, a single word can have double meanings and it could be either positive or negative. Different analysts might give a different set of positive or negative percentage to a particular word with double meanings. This algorithm usually does not deal with multiple words that have various contexts.

  • Natural Language Processing– Natural Language Processing (NLP) is basically computer systems those have the ability to process human language to decipher meanings. This system understands that a couple of words make a phrase and a couple of phrases make a sentence. A couple of sentences convey a particular thought or an idea that needs to be interpreted. NLP works by processing the text and analyzing the language to understand the meaning. This system is popularly used to convert speech into text, checking grammar and translating the language. The algorithm is used to interpret the English language as per its rules mentioned. It is considered to be a superior algorithm that effectively processes the keywords but it has its fair share of limitations. Sarcasm and jargons still remain the problem areas where NLP has difficulty in detecting the true meaning.

Sentiment analysis in social media seems like a tough nut to crack and that is when you need the right help from technology and different algorithms that will make the processes easy. It is also important to understand that the accurate data analysis is important to enjoy growth.

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