Monthly Archives: April 2017

Building a Twitter Clone with Neo4j – Part Six

We are getting close to wrapping up the back-end API for our Twitter clone, so thank you for sticking with this awfully long series since the beginning. One of the big community features of Twitter is the Trending Hashtags. It lets users know what is being talked about even if the people a user follows aren’t talking about it. It’s kind of weird in that way since part of the point of Twitter is following just a few hundred or thousand people to reduce the noise, and here we are bringing noise back in to our feed. Regardless, this is actually pretty easy to implement, so let’s have a crack at it.
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Building a Twitter Clone with Neo4j – Part Five

In part four, we continued cloning Twitter by adding hashtag and mentions functionality. Then we went beyond it by adding the ability to edit a post. So we have a social network where people can follow each other and post stuff. Today we’re adding the ability to say a user likes a post, reposts a post and the most important query of all, being finally able to see our feed or timeline.
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Building a Twitter Clone with Neo4j – Part Four

We left off last time having just added the ability to follow people, see who we’ve followed and has followed us, block and unblock people and finally see whom we have put on our naughty list of blocked users. So we have a social network where people can create relationships, but they have nothing to say because we haven’t implemented that yet!
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Building a Twitter Clone with Neo4j – Part Three

In part two we defined our API and got registering a user, checking a user and getting a user profile. A social network of unconnected people doesn’t live up to its name, so let’s go ahead and build the ability to follow people.

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Building a Twitter Clone with Neo4j – Part Two

One of the aspects of my job that I love is the week long proof of concept bootcamps. What it entail is me (or one of my team members) coming onsite to work with your team to build out a POC in just one week. They all vary some what, but I try to stick to a formula that works for me. I spend the first day with the whole team ironing out the Model. This is the trickiest part to get right, because if the model is right, the queries will fall right into place. If the model has to be changed significantly on day 3 let’s say, then a ton of work has to be redone or at least greatly modified. The goal of the end of day one is to have something that looks like the following:
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