Wizikey brings the world's first metric to measure news visibility - ‘News Score’. See how your brand ranked this month.
Written by Team Wizikey
November 17, 2021
Wizikey’s Sentiment Analysis lets you quickly decide if a brand is trending to positive, negative, or neutral. Learn more.
News Sentiment Analysis is a technique for measuring the opinion of the news. Wizikey’s Sentiment Analysis lets you quickly decide if a brand is trending to positive, negative, or neutral. The powerful metric allows you to make sense of large volumes of news to find trends and correlations.
It is not just the quantity of the new generated that matters, but the quality. Are your stories able to create positive sentiment about your brand? It provides insights into how media perceives your brand. To get a clearer picture, we filter out the generic stories and only look at stories that feature and talk about brands in your competition set.
Sentiment analysis allows for the recognition of words/phrases to their associated emotions. This gives an easy-to-understand overview of the specific characteristics of the sentiment. You can gain insight into the opinion leaders in your niche by reviewing their news articles. There are many different methods to analyzing news articles, but the basis for this method is to find the recurring trends in text.
When it comes to making decisions based on news stories or other content, we all want to be confident that we are getting the most important and accurate information. An automated sentiment analysis engine could provide a system of checks and balances to not only keep us informed but to manage our own perception of the news media.
Sentiment analysis has manifold benefits.
If you would want to know more, reach out to our team at Wizikey.
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Wizikey saves time by bringing relevant brand mentions from news, blogs, podcasts and other mediums in one place. It provides insights to build better awareness. It is built by communications' professionals who struggled with excel sheets, clunky software and decided to solve it themselves.
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