Get More Relevant Data with Webhose Enriched News API
For many organizations, keeping up with the constant stream of online news articles has become extremely challenging, if not impossible.
A ready-made, customized news feed that can be instantly plugged into their application and quickly customized to suit customer’s needs is ideal for filtering the most relevant data. This is true whether your organization is putting their time and resources into enriching news data themselves from scratch or customizing their own NLP-enriched data.
Presenting Webhose Enriched News API
Webhose Enriched News API’s mission is to provide this enriched news data for organizations, saving them countless hours and significant resources that could be better spent on product development. We do this by collecting the most relevant news data from the top 50,000+ global news sources and extracting, mapping, and normalizing multiple data fields. These fields include author, videos, images, external links, publication date, comments, and full post text. This data is critical for organizations providing media monitoring, risk intelligence, or financial analytics to their customers. Not only do these types of solutions rely on high-quality, accurate data, but they also need to have a greater understanding of the context and sentiment of news data for their intelligence applications, analysis of the voice of the customer, competitive intelligence, and more.
For existing customers who want to see these examples for themselves or try out their own queries, check out our API Playground.
Below is an overview of these features with specific examples.
Automation Delivers Relevant News Faster
As the volume of news data increases, it has become more challenging to sift through the massive amount of data and find the most relevant news. Webhose’s deeper level of entity detection helps to detect news events that would otherwise require more complicated queries. For example, it can quickly detect news events like acquisitions, funding, potential fraud, and adverse media to help organizations continually identify the news data that is the most important for them.
For example, if the accounting firm Ernst and Young wanted to monitor their clients for adverse media, they’d need to find a link between a specific individual or entity and their involvement in money laundering, corruption, sanctions exposure, terrorism and threat financing, or any other unlawful activity.
To quickly identify articles linking their clients to adverse media, they would simply use the query:
article.category:*crime* AND (“wirecard” OR “luckin coffee”)
Another way that Webhose’s Enriched News API’s automated search engine delivers more relevant results is by tracking article categories according to the Interactive Advertising Bureau (IAB) and International Press Telecommunications Council (IPTC) taxonomies.
The IPTC taxonomy is a universally accepted standard that categorizes news data like text, photos, and videos. The IAB taxonomy sets a standard for the advertising industry. This type of categorization is crucial for quickly understanding the greater context behind news articles.
Get Greater Context with NLP-Enriched Data
Here’s an example that illustrates why understanding the news data within a greater context is crucial. Let’s say you’ve identified potential fraud activity related to your customers and now you want more of an understanding of the bigger picture: Are other organizations behind that fraud activity. Are there conflicts of interest? These are the types of questions we can answer through NLP-enriched data.
Smart Entity Extraction
Webhose’s Enriched News API gives you this greater context with smart entity extraction that provides an advanced classification of entities according to type, sentiment, relevance, frequency, language, location, and more. You can also combine entities in your query to fine-tune the news data you are looking for.
For example, to find negative mentions specifically of the Nikon brand rather than the camera, you would use the query:
Another way the Enriched News API puts things in perspective is through its ability to recognize different types of sentiment, beyond negative and positive. These types of sentiment include polarity, agreement, subjectivity, irony, and confidence.
Here is an example of how the API measures the different levels of sentiment for an article below:
Mainstream media already classifies news articles into more than 1300 different categories such as politics, sports, and economics. It also lets you break that category down further, to see articles that pertain to more relevant searches, such as sports – basketball – NBA. This type of classification is critical for organizations that want to provide higher-level analysis to their customers.
Let’s say you’d like to search for a video related to racism. You’d use the query:
article.media.has_video:true AND article.category:racism
Another method you can use to understand the greater context is through the labels of the videos and images related to your search. Webhose’s Enriched News API enables you to detect text contained in images that are powered by computer vision.
If you’d like to search for images that contain an iPhone in the image. You’d use the query:
These are a few examples of the types of queries that leverage NLP-enriched data to provide greater context to your searches.
Webhose Enriched News API also offers a ready-made news feed for organizations that need relevant news feeds customized to their customer’s needs. Organizations can simply plug a data feed into their application without having to build their own storage and search engine. The plug and play search engine also provides deduplication of the same stories, like PR articles published on multiple outlets with minimal changes to the text. It also enables you to easily find similar stories, so once you find the relevant news data you are looking for, you can easily expand that search to other related stories.
Towards a More Intelligent AI Application
The AI industry will be worth $118 billion by 2025. That means if your organization isn’t already working on an AI application, it probably will be soon.
With so many organizations competing in the same space, timing is crucial. Sometimes a delay of a product release by a few weeks can be the difference between success and failure. The last thing you want to do is spend countless hours and vast resources on data enrichment and miss out on the right market conditions for your product.
Or maybe your enterprise-level organization is already enriching their data with NLP processing, but you need to take it up a notch.
Whether you’re looking to get started collecting NLP-enriched data for the first time, or you want to enhance an existing offering, Webhose’s Enriched News API can help.
Want to get started infusing high-quality NLP-enriched news with minimal effort from your team? Contact our data experts today!