With the world’s media now publishing news content at web scale, it’s possible to leverage this content and discover what news the world is consuming in real time. Using the AYLIEN News API, you can both look for high-level trends in global media coverage and also dive into the content to discover what the world is talking about.
So in this blog we’re going to take a high-level look at some of the more than 2.5 million stories our News API gathered, analyzed, and indexed last month, and see what we find. Instead of searching for stories using a detailed search query, we’re simply going to retrieve articles written in English and see what patterns emerge in this content.
To understand the distribution of articles published over time, we’ll use the Time Series endpoint. This endpoint allows us to see the volume of stories published over time, according to whatever parameters you set. To get an overview of recent trends in content publishing, we simply set the language parameter to English. Take a look at the pattern that emerges over the past two months:
The first thing you’ll notice is how steady the publishing industry’s patterns are – there is a steady output of around 60,000 new stories in English every weekday, dropping to about 30,000 stories on weekends. This pattern is very regular, except in the last week of the month, when a small but noticeable spike in story volume occurs.
What caused this spike in story volume?
To find the cause of these extra 2,000 – 4,000 stories, we browsed the volume numbers of the biggest categories to see if we could identify a particular subject category which followed the same pattern. We found an unmistakable match in the Finance category – as well as taking place in the same period, this spike also matches the volume of extra stories – roughly an extra 2,000 stories above the daily average.
In addition to this, we also found a similar spike at the end of July. Take a look at the daily story volume of finance stories published over the past six months:
What topics were discussed in this content?
Knowing that the increase in story volume in the last week of October was due to a spike in the number of Finance stories is great, but we can go further and see what was actually being talked about in these stories. To do this, we leveraged our News API’s capability to analyze the keywords, entities and concepts mentioned. The News API allows you to discover trends like this in news stories using the Trends endpoint.
Analyzing keywords lets us get an overview of what people, organizations, and things are mentioned most in the roughly 10,000 finance stories published in that week. Looking at the chart below, it’s a pretty easy to see what caused the spike.
From the results shown in the bubble chart it’s easy to see that keywords and concepts like “quarter”, “earnings”, “financial” and “company” were identified. From this analysis we can make a good guess that a lot of this content published in the last week of October was related to quarterly results and financial reporting by companies. This makes a lot of sense, since in the Time Series chart we could see that a similar spike occurred at the end of July, three months ago.
We thought this was interesting – why was so much published about something so arcane to the general public? In the first graph, we could see the spike that these quarterly earnings reports caused on story volume was visible on a chart of all stories published in the English language. But we don’t think quarterly earnings reports would make the everyday news content consumer drop everything they are doing to check the news.
Why were people interested in quarterly earnings reports?
So we know from the spike in story volume that the media were interested in the quarterly earnings reports. But what were social media users interested in? To find out, we decided to gather the most-shared stories from the Finance categories from the last week of October – the week of the spike. This will tell us if there was a particular aspect to the earnings reports that prompted such a spike in this topic.
The News API lets us do that with the Stories endpoint, by simply searching for the most-shared stories from the Finance category during last week of October across Facebook, LinkedIn, and Reddit.
You can see that of the nine stories we gathered, five are about the earnings reports, and despite this being quite a business-focused topic, Facebook was the network that this content was most popular on, not LinkedIn.
- “Swiss bank UBS reports 14 percent growth in 3Q net profit,” Associated Press, 39,907 shares
- “Amazon shares soar as earnings beat expectations,”Associated Press, 39,870 shares
- “US stocks higher as banks and technology companies rebound,” Associated Press, 39,867 shares
- “Jeff Bezos is now the richest man in the world with $90 billion,” CNBC, 7,318 shares
- “CVS Reportedly Looking To Buy Aetna Insurance For $66 Billion,” Consumerist, 2,172 shares
- “New Uber Visa Credit Card From Barclays Coming Next Week,” Forbes, 1,967 shares
- “First reading on third-quarter GDP up 3.0%, vs 2.5% rise expected,” CNBC, 14,807 upvotes
- “New study says Obamacare premiums will jump in 2018 — in large part because of Trump,” Business Insider, 6,255 upvotes
- “MSNBC host literally left his seat to fact-check Jim Renacci,” Cleveland, 4,641 upvotes
You can see above that of the nine most-shared stories on social media on the week of the spike caused by the quarterly earnings reports, only five actually mention the reports. This suggests to us that although the media published a huge amount on the reports, people in general weren’t too interested in them.
Since we are basing this assumption on just a few headlines above, it’s just a hunch. But with the News API, we can put hunches like this to the test by analyzing quantitative data.
Exactly how interested were people in quarterly earnings reports?
In order to bit more accurate about how interested people were in the quarterly earnings reports, we compared the share counts of the 100 most-shared stories from the week of the spike with those from the corresponding week last month. We can do this using the News API’s Stories endpoint, since the News API monitors the share count of every story it indexes. Also, we’re going to look at Facebook since in the previous section it was the social network most interested in the quarterly earnings reports.
Take a look at how often people were sharing the 100 most-shared stories on Facebook in the last week of October:
You can see that people were sharing Finance stories less often in the last week of October than the same period in September. This is interesting because we already saw that that there were over three times more Finance stories published in the same period, so we have to assume that people on social media generally just weren’t interested in these stories.
This piece of information is interesting because it shows us that looking at viral stories about a subject can mislead us about how interested people are about that subject.
Well that concludes this month’s roundup of news with the News API. If you want to dive into the world’s news content and use text analysis to extract insights, our News API has a two-week free trial, which you can activate by clicking the link below.