What is Sentiment Analysis?
Sentiment analysis is using NLP (Natural Language Processing) techniques to determine whether data is positive, neutral or negative. News sentiment analysis helps brands and businesses monitor sentiment in article headlines and content.
What is News Sentiment Analysis?
By monitoring news, you can extract references and mentions about your brand or business from the media. In News sentiment analysis, you analyze a news article and the content to identify a sentiment – positive, negative or neutral. This helps you understand how the public feels about your company.
Why Is News Sentiment Analysis Important?
News sentiment analysis is extremely important because it allows businesses to understand the sentiment of how their brands are portrayed. By sorting the sentiment behind news headlines, content, reviews, and more, brands can make better and more informed decisions.
It’s estimated that 90% of the world’s data is unstructured and unorganized. Huge volumes of similar unstructured data are created every day and it’s impossible to analyze sentiments effectively and efficiently. We need streamlined power-packed NLP APIs to do the job for us in a timely and efficient manner.
Read: 21 Best Sentiment Analysis Tools for 2021
The overall benefits of news sentiment analysis include:
- Sorting Data at Scale
Can you imagine manually sorting through thousands of different kinds and types of content? A key part of maintaining a brand’s reputation is through constantly monitoring how it is perceived You’ll have to keep an eye on news feeds, news sites, and so much more. This is just too much data to process manually. News sentiment analysis can help businesses process huge amounts of data in an efficient and cost-effective way.
- Real-Time Analysis
Sentiment analysis can identify critical issues in news articles in real-time. Find out when and where your brand has been mentioned and if the sentiment is immensely negative, you can immediately identify and take action right away.
- Consistent criteria
Tagging text or here, news headlines by sentiment is highly subjective, influenced by personal experiences, thoughts, and beliefs. By using a centralized sentiment analysis system, companies can apply the same criteria to all of their data, helping them improve accuracy and gain better insights with text analysis.
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Why choose Social Animal’s News API for news sentiment analysis?
Social Animal‘s News API is blazingly fast and provides global news, trending headlines, popular web content from millions of news sources in real-time using machine learning and Natural language processing techniques. The advanced filters in Social Animal’s API make it one of a kind as it lets you narrow down the exact content you need. One of the most popular filters used is the narrowing down of articles based on their performance on different social media platforms. Other filters include filtering by keywords, title, date, language, location, word count, author names, domain, published vs shared dates, TLD, URLs, or even by the type of content – Listicle, Product review, How to guide, Podcast, etc. This is one of the very few News APIs that offers sentiment analysis for news headlines and the content.
- Get timely identification of brand mentions across various forms of media including news articles, blogs, reviews and more.
- Automate a laborious and time-consuming task.
- Offers a robust tracking of online news across thousands of websites.
- Gain insights into the press’ opinion of your brand.
- Data to compare your performance against your competitors.
- Identification of issues and trends before they impact your brand.
- Improve your business by identifying areas of improvement.
- Track and monitor sentiments related to any keyword, or topic.
- Gauge overall public sentiment about a topic or product from news data.
- If a negative sentiment develops, you can spot it early and set in motion corrective measures.
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Other news sentiment analysis APIs:
Repustate:
Repustate’s News sentiment analysis solution helps you listen to and analyze customer feedback across all channels so you can improve your products and services and delight your customers. It also lets you create sentiment analysis rules that are specific to your industry and unique business use cases.
Connexun’s Text Analysis API
Connexun’s sentiment analysis evaluates if a given text is positive, negative or neutral. The API returns a sentiment score for any text in English. The score may be negative or positive, with greater values representing a more negative or more positive nature of the text. A score closer to 0 (zero), on the other hand, reflects a more neutral tone of the sentence.
Conclusion
Sentiment analysis has moved beyond interesting and will soon become an indispensable tool for all companies of the modern age. News sentiment analysis helps glean new insights, better understand customers, and empower teams.
