Political Opinion Mining: Measuring People’s Opinion Before Hitting the Bulls Eye

Opinion inversion is often employed by politicians who look to mold public perception when it goes against them.

This allows them to win the votes of their opposite candidate, flipping the opinion of the general public in their favor.

Social media is one of the most pursued tools for the purpose of opinion conversion as it allows politicians to do sentiment analysis and deploy efficient strategies to tackle the deteriorating reputation.

Tricks to do Political Opinion Mining for your Political Campaign

Sentiment analysis, or as it is popularly known, Natural Language Processing (NLP) technique and opinion mining, most often work on machine learning principles that automatically measure the emotional tone of the people commenting on online platforms.

Different algorithms can be implemented in sentiment analysis. Three major principles on which political sentiment analysis depend are:

Rule-based:

According to this regime, sentiment analysis is done using manually crafted rules.

Automatic System:

In the automatic measurement of sentiment analysis, machine learning provides feasible grounds to measure the emotional tone of people, which can then be incorporated in modifying the course of your political campaign.

Hybrid systems:

As the name suggests, hybrid systems incorporate the principles of both rule-based and automatic responses.

Rule-Based Opinion Mining and Sentiment Analysis: Simple but Labor Intensive Strategy

Many campaigns which deploy rule-based opinion mining strategies have to identify challenges and maintain their objectivity throughout the course of their campaigns.

They accomplish this by neglecting the inherited bias that may arise with the political association.

First, political campaigns have to define two lists of words extremely opposite in nature. In the sense of a political campaign, bad words can include inefficient, worst, or poor leader and other words and phrases along the same lines.

Contrary to this, positive words can include good leader, efficient, and problem-solver, and other similar words.

Once you gather all the comments of people who are to be measured, all you have to do is to count the number of negative and positive words.

While in a small number of texts, it is technically possible to do it manually. However, as political campaigns are the recipient of these sorts of comments from all sectors of societies and even countries, doing this manually is absolutely no option.

At this point, you have to engage with the technology to count these sentiments for you.

So algorithms will make your job easy and bring the amount of positive and negative sentiments for your campaign visible in a matter of a few seconds.

Machine Learning Technologies: The Way to go for Modern Political Campaigns

One of the most prominent negative aspects of rule-based systems is that it does not entertain the combination of words that may be used to express the same opinion which your sorted out words would make.

Even if you have already defined a list of words, you won’t be able to get the actual results. Machine learning algorithms have become important, which incorporates the complexity of language and understands the different combinations of words which is not possible through the labor-intensive rule-based method.

Machine learning political opinion mining is simple. It is a process of empowering machines so that they can divide the text into either black or white category.

The frequency with which either positive or negative words are used is also essential as it predicts how much your voter supports or opposes your campaign.

Machine learning is perhaps the best method available today to dig deep and extract every possible opinion of people to know in which direction your campaign is going.

Final Thoughts

In any political campaign, data mining has become a necessity, as marketing your candidacy without relying on data is always a blind shot that is likely to end in failure.

This reinforces the importance of sentiment analysis, as it will help you bell the cat before it eats up your whole campaign.

Opinion inversion is only possible when you know what is the opinion of the general public in the first place.

Without knowing the opinion of your voters, inverting it is not even possible. So every reputation management campaign is preceded by sentiment analysis, which makes the job of reputation managers easier.