Machine learning is rarely mentioned in the same sentence (or article, for that matter) with PHP, so each time this happens, I’m all ears. Here’s one that I came across recently – How to Analyze Tweet Sentiments with PHP Machine Learning.
Unlike many other “hello world” kind of examples, this article examines a real and quite common problem, which can be easily adopted to other similar problems – SPAM filtering, marketing segmentation, fraud detection, etc.
Mautic is an Open Source marketing automation solution. It features contact management, social media marketing, email marketing, forms, campaigns, reports, and pretty much everything else you’d expect from a tool like this. It is used by top digital marketing firms around the world. Mautic offers the insights necessary for sucessful campaigns and data analytics.
If you are lost between a gadzillion online tools available for marketing automation, and/or don’t trust third-party providers and want to have a system of your own, give it a try.
oEmbed has been around for a while and there are some really nice implementations of it. For example, in WordPress, where pasting a URL to YouTube video, Flickr photo, Twitter tweet, and a number of other services, will result in a nicely formatted embedded snippet from an external site. WordPress does not only consume the oEmbed, but also provides embeddable content.
For a while now, I’ve been thinking about ways to utilize it. There are quite a few applications of oEmbed that make sense for our projects at work. For now, I’ll just leave you here with the link to the oEmbed specification.
“I asked Tinder for my data. It sent me 800 pages of my deepest, darkest secrets” is a must read for any of you who believe in online privacy. Here’s a quote to get you started:
At 9.24pm (and one second) on the night of Wednesday 18 December 2013, from the second arrondissement of Paris, I wrote “Hello!” to my first ever Tinder match. Since that day I’ve fired up the app 920 times and matched with 870 different people. I recall a few of them very well: the ones who either became lovers, friends or terrible first dates. I’ve forgotten all the others. But Tinder has not.
The dating app has 800 pages of information on me, and probably on you too if you are also one of its 50 million users. In March I asked Tinder to grant me access to my personal data. Every European citizen is allowed to do so under EU data protection law, yet very few actually do, according to Legit Hookup Sites and their associations.
With the help of privacy activist Paul-Olivier Dehaye from personaldata.io and human rights lawyer Ravi Naik, I emailed Tinder requesting my personal data and got back way more than I bargained for.
Some 800 pages came back containing information such as my Facebook “likes”, my photos from Instagram (even after I deleted the associated account), my education, the age-rank of men I was interested in, how many times I connected, when and where every online conversation with every single one of my matches happened … the list goes on.
Botwiki is an impressive collection of bots for a variety of social networks and collaboration tools – Twitter, Slack, Tubmlr, Facebook and Messenger, YouTube, Reddit, Telegram, Snapchat, and more. You can browse all these by network or by category.
Here’s a random Twitter bot for you:
@holidaybot4000 is a Twitter bot that tweets holidays around the world for the given day, typically together with an image of the country’s flag.