7 Ways To Use Big Data To Your Advantage On Social Media

Businesses can use big data in many capacities, but those who use it for social media are at a huge advantage. It enables you as a social media marketer to get a closer look at your customer base, understand what drives purchasing decisions, and encourage consumers to pull the trigger.

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Re-exporting the magrittr pipe operator

… or how I stoped worrying and wrote a blog post to remember it ad infinitum.
Magrittr’s pipe operator is one of those newish R-universe features that I
really want to have around whenever I put some lines into an R-console.
This is even TRUE when writing a package.
So the first thing I do is put magrittr into the DESCRIPTION file and add
an __imports.

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Trump as stressor — Shep Smith edition

This is another one of those threads that goes back three of four years. The conservative movement’s media strategy proved to be remarkably effective for a long time, but there waere always tensions and potential instability.It only worked as long as things weren’t pushed too far. With the mainstream press this meant keeping the spin just within the bounds of plausibility.

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Recap of my first Kaggle Competition: Detecting Insults in Social Commentary [update 3]

Recently I entered my first kaggle competition – for those who don’t know it, it is a site running machine learning competitions. A data set and time frame is provided and the best submission gets a money prize, often something between 5000$ and 50000$.I found the approach quite interesting and could definitely use a new laptop, so I entered Detecting Insults in Social Commentary.

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(Excerpts from) ‘P-Value Thresholds: Forfeit at Your Peril’ (free access)

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A key recognition among those who write on the statistical crisis in science is that the pressure to publish attention-getting articles can incentivize researchers to produce eye-catching but inadequately scrutinized claims. We may see much the same sensationalism in broadcasting metastatistical research, especially if it takes the form of scapegoating or banning statistical significance.

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Bot or Not: an end-to-end data analysis in Python

For those who didn’t make it to my PyData talk… how dare you? Aww, I can’t stay mad at you. Here’s the written version of my talk about building a classifier with pandas, NLTK, and scikit-learn to identify Twitter bots. You can also watch it here.
In this post I want to discuss an Internets phenomena knows as bots, specifically Twitter bots.

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ICML 2017 Thoughts

ICML 2017 has just ended. While Sydney is remote for those in Europe and North America, the conference centeris a wonderful venue (with good coffee!), and the city is a lot of fun. Everything went smoothly and the organizers did a great job.You can get a list of papers that I liked from my Twitter feed, so instead I’d like to discuss some broad themes I sensed.

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Automating ethics

Machines will need to make ethical decisions, and we will be responsible for those decisions.We are surrounded by systems that make ethical decisions: systems approving loans, trading stocks, forwarding news articles, recommending jail sentences, and much more. They act for us or against us, but almost always without our consent or even our knowledge.

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Let’s look at groups: the same issue is experienced differently

In our last post, we talked about identifying Topics. Today we are going to explore the importance of looking at how those topics change with different groups of consumers. You can define a Group by many factors, including; geography, purchase frequency, age, gender, and many more.

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