What you need to know
App developers in both Asia and the US are finally taking advantage of the echo-sized gap in the market for a balanced news diet.
Veeoz (pronounced “Views”) is a news app that promises to protect users from “fake news” and counter social media echo chamber issues, irrespective of language differences. A key component of the Veooz offering is users’ ability to see all around an issue via related stories. “Even if the article – e.g. Breitbart News – is trying to spin a different point of view, I can counterbalance in [the app’s] 360 view showing all the other articles from different sources,” says Veooz Founder and CEO Srini Koppolu.
Meanwhile, in the U.S., developers launched a Kickstarter campaign under the tagline “Burst Your Filter Bubble” to attract more than $5,000 to fund their Read Across The Aisle app, which is designed to “combat political polarization.” The app swiftly broke into the top 100 downloads in the App Store’s News category upon its release at the start of March. The app ranks 20 media outlets in terms of their position on the political spectrum, and then tracks the time spent consuming content from each one, allowing the user to moderate their intake and avoid bias.
Expect similar technology to feature strongly in the release of news and media apps as the world wrestles with problems related to social media filtering, and what former President Barack Obama warned in his farewell address represents a “retreat into bubbles.”
Veeoz, which is based in the Indian city of Hyderabad, takes a less politicized approach but deals with a much larger range of sources than Read Across The Aisle, trawling more than 100,000 articles each day and using the top three or four paragraphs to “cluster” the story into preferences. It claims to serve only stories generated by authoritative sources, as determined by an algorithm that discards infrequent posters, and a human editorial team focused on compiling lists of trusted outlets.
Major media publishers feeling the strain of falling readership and advertising numbers should welcome the potential extra eyeballs. In December, Dow Jones CEO Will Lewis said in a Drum interview that Facebook and Google are “killing news,” partly due to the echo-chamber nature of their algorithms, but also the inability of subscription based digital publications like The Wall Street Journal to feature highly on search results. Under Google’s First Click Free program their publication – and by extension all those operating a pay-to-consume-quality news model – fail to reach a wider audience because they are excluded from Google's leading search results.
It’s a gap in the market that Koppolu, a former VP with Microsoft India Development Center, hopes to exploit via advertising partnerships. “My pitch is if you are building an app – you can attract your audience, but search and news aggregators [lik Veooz] will have a broad audience, and we can bring you that additional traffic,” he told The News Lens in Taipei.
Veooz currently has 600,000 downloads, grounded in a primarily Indian readership, having launched a few weeks ago to solid initial user retention and engagement numbers. It is seeking investment to expand in Southeast Asia.
Koppolu is banking on investors understanding the potential of billions of first-time smartphone users across India and Asia wanting to consume content in their native language, particularly as India’s internet user penetration is forecast to reach only a third this year, according to market research firm eMarketer. He says the app also does a good job of determining how to serve stories in less commonly used internet languages, including Tamil, Telugu and Bahasa Indonesia, by cross referencing the language with the frequency of posting or sharing in a specific geography. This location-based focus also helps introduce stories outside a user’s specified preferences. “To avoid tunnel vision, we add the top trending stories of the place the user is in, as well as anything big that’s happening in the world, and that can result in them following more interests.”
Serving on-topic news with a varied degree of sources seems like the kind of problem tech should be able to solve, but news by its nature is one of the hardest nuts to crack when it comes to machine learning, according to Koppolu. “The hardest thing is understanding how complex a problem news is," he says. "We have amazing summarization technology and it works really well in a specific domain because you are learning over and over again, but with news there is no domain – everything is news – and when you bring it to a new language, it’s a huge challenge.”
Editor: Edward White