Local News Dataset 2018

By Leon Yin
On 2018-08-14

Introduction

This dataset is a machine-readible directory of state-level newspapers, tv stations and magazines. In addition to basic information such as the name of the outlet and state it is located in, all available information regarding web presence, social media (twitter, youtube, facebook) and their owners is scraped, too.

The sources of this dataset are usnpl.com-- newspapers and magazines by state, stationindex.com -- tv stations by state and by owner, and homepages of the media corporations Meredith, Sinclair, Nexstar, Tribune and Hearst.

This dataset was inspired by ProPublica's Congress API. I hope that this dataset will serve a similar purpose as a starting point for research and applications, as well as a bridge between datasets from social media, news articles and online communities.

While you use this dataset, if you see irregularities, questionable entries, or missing outlets please submit an issue on Github or contact me on Twitter. I'd love to hear how this dataset is put to work

Happy hunting

For an indepth introduction, specs, data sheet, and quickstart check out this Jupyter Notebook in nbs/local_news_dataset.ipynb.

What's the data look like?

	name	state	website	domain	twitter	youtube	facebook	owner	medium	source	collection_date
0	KWHE	HI	http://www.kwhe.com/	kwhe.com	NaN	NaN	NaN	LeSea	TV station	stationindex	2018-08-02 14:55:24.612585
1	WGVK	MI	http://www.wgvu.org/	wgvu.org	NaN	NaN	NaN	Grand Valley State University	TV station	stationindex	2018-08-02 14:55:24.612585
2	KNIC-CD	TX	NaN	NaN	NaN	NaN	NaN	Univision	TV station	stationindex	2018-08-02 14:55:24.612585

You can also browse the dataset on Google Sheets
Or look at the raw dataset on Github
Or just browse the Jupyter Notebook's tech specs.

How is this Repo Organized?

The nbs directory has exmaples of how to use this dataset. The dataset was created in Python. The scripts to re-create and update the dataset are in the py directory.. In addition to the state and name of each media outlet, I also collect their web domain and social (Twitter, Facebook, Youtube) IDs where available.

Methodology

Several websites are scraped using the requests and beautifulsoup Python packages. The column names are then normalized, and merged.

Gotchas

There can be several entires with the same domain.
Why? Certain city-level publications are subdomains of larger state-level sites. There is a preprocessed version for domain-level analysis here: https://raw.githubusercontent.com/yinleon/LocalNewsDataset/master/data/local_news_dataset_2018_for_domain_analysis.csv

Using the Dataset

The dataset can be downloaded from the raw GitHub file using the website, or from the commandline:

wget https://raw.githubusercontent.com/yinleon/LocalNewsDataset/master/data/local_news_dataset_2018.csv

The dataset can also be loaded directly into a Pandas DataFrame.

import pandas as pd

url = 'https://raw.githubusercontent.com/yinleon/LocalNewsDataset/master/data/local_news_dataset_2018.csv'
df_local_news = pd.read_csv(url)

Acknowledgements

I'd like to acknowledge the work of the people behind usnpl.com and stationindex.com for compiling lists of local media outlets. Andreu Casas and Gregory Eady provided invaluable comments to improve this dataset for public release. Leon Yin is a member of the SMaPP Lab at NYU. Thank you Josh Tucker, Jonathan Nagler, Richard Bonneau and my collegue Nicole Baram.

Citation

If this dataset is helpful to you please cite it as:

@misc{leon_yin_2018_1345145,
  author       = {Leon Yin},
  title        = {Local News Dataset},
  month        = aug,
  year         = 2018,
  doi          = {10.5281/zenodo.1345145},
  url          = {https://doi.org/10.5281/zenodo.1345145}
}

mooreniemi/LocalNewsDataset