In the right architecture, machine-learning functionality takes data analytics to the next level of value. Editor's note: This guest post (translated from Italian and originally published in late 2016) by Lorenzo Ridi, of Google Cloud Platform partner Noovle of Italy, describes a POC for building an end-to-end analytic pipeline on GCP that includes machine-learning functionality. "Black Friday" is traditionally the biggest shopping day of the year in the United States. Black Friday can be a great opportunity to promote products, raise brand awareness and kick-off the holiday shopping season with a bang. During that period, whatever the type of retail involved, it's also becoming increasingly important to monitor and respond to consumer sentiment and feedback across social media channels.
Video watching had emerged as one of the most frequent media activities on the Internet. Yet, little is known about how users watch online video. Using two distinct YouTube datasets, a set of random YouTube videos crawled from the Web and a set of videos watched by participants tracked by a Chrome extension, we examine whether and how indicators of collective preferences and reactions are associated with view duration of videos. We show that video view duration is positively associated with the video's view count, the number of likes per view, and the negative sentiment in the comments. These metrics and reactions have a significant predictive power over the duration the video is watched by individuals. Our findings provide a more precise understandings of user engagement with video content in social media beyond view count.
This blog was originally published on our Text Analysis blog, the blog post set out to analyze and visualize 11 million tweets collected around the time of and during Apple Live 2014. Apple Live probably got off to the worst start possible earlier this year. Most of us who tried to log on to watch the much-anticipated launch were first, forced to watch the live feed in Safari and second, greeted with the TV Truck Schedule Screen... To add to this Apple also made a complete mess of the audio. We were left sitting refreshing the page, waiting for the stream to start while being subjected to an audio visual nightmare, described brilliantly by this "fan" below: To simulate the #applelive experience, open up several separate YouTube vids, play them simultaneously, minimize, stare at a test pattern. At AYLIEN, we gathered 11 million tweets mentioning'Apple', 'iPhone', 'iOS', 'iPad', 'Mac', 'iPod', 'Macbook', 'iCloud', 'OS X', 'iWatch' and '#AppleLive' from the 4th of September to the 10th of September with a view of analyzing the tweets to gain insight into the voice of Apple Followers.