The Shifting Definition of Newsworthiness

I read Bari Weiss’ resignation letter from the New York Times with some perplexity. In particular, I found her claim that she “was hired with the goal of bringing in voices that would not otherwise appear in your pages” a bit strange: Weiss is, after all, a wealthy graduate of Columbia who’s lived in the Northeast her entire life.

I’ve been playing around with New York Times archive data for some time and wanted to test Weiss’ claim. Has there been a (quantitative) change in the news the New York Times produces, especially since November 2016?

In this post, I’m going to take a look at what we can learn about “all the news that’s fit to print” from the metadata available in the archive — things like word counts, bylines, and news divisions. I’m looking for ways to approximate the “diversity” of the Times’ coverage since 2015. Essentially, we’re looking for real evidence of all those reporters sent to diners in Trump country in 2016 and after.

(For reference, here’s a map of all the IHOPs in the country. IHOP seemed like a good proxy for diners generally, and Waffle House is too concentrated in the south to be meaningful nationwide — it’s actually not that far off from what we have.)

Image for post

The New York Times, as the largest and most successful American newspaper (and as far as I can tell, the biggest one with a publicly available API) offers an interesting case for analysis: the Times went to a paywall in 2011, and its emphasis on producing content to fuel subscriptions has accelerated since then; simultaneously, engagement with the Times since Trump’s election has increased steadily. Bari Weiss aside, how has the Times navigated its way through competing currents in media?

#new-york-times #news #python #analytics #data analytic

What is GEEK

Buddha Community

The Shifting Definition of Newsworthiness

Javascript Array Shift Example | Array.prototype.shift()

Javascript array shift() is an inbuilt function that removes the first item from an array and returns that deleted item. The shift() method changes the length of the array on which we are calling the shift() method. Javascript Array Shift method is not  pure function as it directly modifies the  array.

Javascript Array Shift Example

Javascript shift() method removes the item at the zeroeth index and shifts the values at consecutive indexes down, then returns that removed value.

If we want to remove the last item of an array, use the  Javascript pop() method.

If the length property is 0,  undefined is returned.

The syntax for shift() method is the following.

array.shift()

An array element can be a  string, a number, an  array, a boolean, or any other  object types that are allowed in the Javascript array. Let us take a simple example.

#javascript #array.prototype.shift #javascript pop #javascript shift

Lisa joly

Lisa joly

1624071060

Big Data World, Part 1: Definitions

Read this post in other languages:

简体中文

This post is the first in a series about Big Data. In it, we’d like to tell you how we at JetBrains see Big Data, and consequently, how we’re creating products for it.

Next parts:

  1. This article
  2. Big Data World, Part 2: Roles
  3. Big Data World, Part 3: Building Data Pipelines
  4. Big Data World: Part 4. Architecture
  5. Big Data World, Part 5: CAP Theorem

Table of contents:

The world of big data can seem mysterious, hidden behind a curtain of unknown and weird words. It’s time to clear up this mystery and define Big Data.

#big-data #big data world #definitions #big data world, part 1: definitions

Ruth  Nabimanya

Ruth Nabimanya

1624847531

What is Big Data: Definition, Architecture, Characteristics & Use Cases

What is Big Data?

Big Data is all about large and complex data sets, which can be both structured and unstructured. Its concept encompasses the infrastructures, technologies, and tools created to manage this large amount of information. However, the data array with Big prefix is so huge that it is impossible to “shovel” it with structuring and analytics. This is the reason why we need a Platform to understand a set of multiple technologies to Ingest, analyze, search, process a large amount of structured and unstructured information for Real-Time Insights and Data Visualization.

Going Big as in data? You need a Big Data Cloud Strategy

#big data engineering #blogs #hadoop migrations to delta lake #what is big data #definition #what is big data: definition, architecture, characteristics & use cases

Lenora  Hauck

Lenora Hauck

1597467480

Git Installation and Basic Definitions.

This post isn’t going to explain theoretical concepts behind Git — a version-control system usually managed from the command line, though sometimes managed from a GUI (if we’re Windows programmers, which is me, sometimes). Neither is this a post with in-depth insights or sophisticated actions that can be done in Git and nor is it a post that explains Git and GitHub to non-programmers.

Then what is this? It’s a post in which I gathered basic Git settings that I apply when setting up Git on a new server. This will be my — and hopefully your — one-stop-shop for Git initial configuration definitions.

Installation

Let’s start at the beginning — installing Git on a server. Every operating system has its own way of installing Git. Atlassian has a post on its website that lists all the methods for all OSs — Mac, Windows, Linux — and their various flavors. On Centos, which is what’s relevant to me, here is how to install:

sudo yum install git

Configuring the Git User Definitions

Every commit is attributed to a specific user. It is recommended that the user’s username and email be set immediately after installation. This is to prevent this message from appearing on the first commit:

Your name and email address were configured automatically based on your username and hostname. Please check that they are accurate. You can suppress this message by setting them explicitly:

Setting username and password:

git config --global user.name "Your Name"

git config --global user.email you@example.com

If you want to fix the username and password that were used in the commit, you do it using the --amend parameter:

git commit --amend --author='Your Name <you@example.com>'

Colors

Git can paint its commands’ output in beautiful, easy to read colors, instead of just white:

Isn’t easier on the eyes when the hash has a special color, the commit date has a special color, etc.?

Isn’t easier on the eyes when the hash has a special color, the commit date has a special color, etc.?

The easiest way to make this happen is by using running this configuration in the command line:

git config --global color.ui auto

If you want to further enhance it, you can read this answer on unix.stackexchange.

#git #git installation #basic definitions #git user definitions

The Shifting Definition of Newsworthiness

I read Bari Weiss’ resignation letter from the New York Times with some perplexity. In particular, I found her claim that she “was hired with the goal of bringing in voices that would not otherwise appear in your pages” a bit strange: Weiss is, after all, a wealthy graduate of Columbia who’s lived in the Northeast her entire life.

I’ve been playing around with New York Times archive data for some time and wanted to test Weiss’ claim. Has there been a (quantitative) change in the news the New York Times produces, especially since November 2016?

In this post, I’m going to take a look at what we can learn about “all the news that’s fit to print” from the metadata available in the archive — things like word counts, bylines, and news divisions. I’m looking for ways to approximate the “diversity” of the Times’ coverage since 2015. Essentially, we’re looking for real evidence of all those reporters sent to diners in Trump country in 2016 and after.

(For reference, here’s a map of all the IHOPs in the country. IHOP seemed like a good proxy for diners generally, and Waffle House is too concentrated in the south to be meaningful nationwide — it’s actually not that far off from what we have.)

Image for post

The New York Times, as the largest and most successful American newspaper (and as far as I can tell, the biggest one with a publicly available API) offers an interesting case for analysis: the Times went to a paywall in 2011, and its emphasis on producing content to fuel subscriptions has accelerated since then; simultaneously, engagement with the Times since Trump’s election has increased steadily. Bari Weiss aside, how has the Times navigated its way through competing currents in media?

#new-york-times #news #python #analytics #data analytic