All Projects → cdeweyx → Medium-Stats-Analysis

cdeweyx / Medium-Stats-Analysis

Licence: other
Exploring data and analyzing metrics for user-specific Medium Stats

Programming Languages

Jupyter Notebook
11667 projects
python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to Medium-Stats-Analysis

imbalanced-ensemble
Class-imbalanced / Long-tailed ensemble learning in Python. Modular, flexible, and extensible. | 模块化、灵活、易扩展的类别不平衡/长尾机器学习库
Stars: ✭ 199 (+637.04%)
Mutual labels:  data-mining
MetQy
Repository for R package MetQy (read related publication here: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6247936/)
Stars: ✭ 17 (-37.04%)
Mutual labels:  data-mining
hierarchical-clustering
A Python implementation of divisive and hierarchical clustering algorithms. The algorithms were tested on the Human Gene DNA Sequence dataset and dendrograms were plotted.
Stars: ✭ 62 (+129.63%)
Mutual labels:  data-mining
Data-Mining-on-Social-Media
Python scripts to extract tweets and facebook posts from public users.
Stars: ✭ 99 (+266.67%)
Mutual labels:  data-mining
Heart disease prediction
Heart Disease prediction using 5 algorithms
Stars: ✭ 43 (+59.26%)
Mutual labels:  data-mining
conferencias matutinas amlo
CSVs de las versiones estenográficas de las conferencias matutinas del Presidente Andres Manuel López Obrador ( Mañaneras AMLO )
Stars: ✭ 25 (-7.41%)
Mutual labels:  data-mining
Semantic-Bus
object flow treatment, data transformation
Stars: ✭ 49 (+81.48%)
Mutual labels:  data-mining
data-exploration-with-apache-drill
Data Exploration with Apache Drill
Stars: ✭ 25 (-7.41%)
Mutual labels:  data-mining
TextClassification
基于scikit-learn实现对新浪新闻的文本分类,数据集为100w篇文档,总计10类,测试集与训练集1:1划分。分类算法采用SVM和Bayes,其中Bayes作为baseline。
Stars: ✭ 86 (+218.52%)
Mutual labels:  data-mining
scikit-cycling
Tools to analyze cycling data
Stars: ✭ 25 (-7.41%)
Mutual labels:  data-mining
PaperWeeklyAI
📚「@MaiweiAI」Studying papers in the fields of computer vision, NLP, and machine learning algorithms every week.
Stars: ✭ 50 (+85.19%)
Mutual labels:  data-mining
perke
A keyphrase extractor for Persian
Stars: ✭ 60 (+122.22%)
Mutual labels:  data-mining
corpusexplorer2.0
Korpuslinguistik war noch nie so einfach...
Stars: ✭ 16 (-40.74%)
Mutual labels:  data-mining
Asclepius
Open Price Comparison for US Hospitals
Stars: ✭ 20 (-25.93%)
Mutual labels:  data-mining
KaliIntelligenceSuite
Kali Intelligence Suite (KIS) shall aid in the fast, autonomous, central, and comprehensive collection of intelligence by executing standard penetration testing tools. The collected data is internally stored in a structured manner to allow the fast identification and visualisation of the collected information.
Stars: ✭ 58 (+114.81%)
Mutual labels:  data-mining
sugarcube
Monoidal data processes.
Stars: ✭ 32 (+18.52%)
Mutual labels:  data-mining
dh-core
Functional data science
Stars: ✭ 123 (+355.56%)
Mutual labels:  data-mining
iis
Information Inference Service of the OpenAIRE system
Stars: ✭ 16 (-40.74%)
Mutual labels:  data-mining
sciblox
sciblox - Easier Data Science and Machine Learning
Stars: ✭ 48 (+77.78%)
Mutual labels:  data-mining
awesome-Python-data-science-books
Probably the best curated list of data science books in Python
Stars: ✭ 331 (+1125.93%)
Mutual labels:  data-mining

Medium-Stats-Analysis

Getting Started

The goal is to collect baseline stats on stories from Medium Stats in order to get a better understanding of how readers engage with a writers work. Note that this is a personal project and is in no way associated with Medium. In order to best utilize this repo, follow the following directives depending on your goals. If the Jupyter notebooks give you trouble rendering, just copy/paste the url into nbviewer and it should work.

See the Post

I wrote a Medium post as well. You can find the post and more about metrics on Medium here:

Deconstructing Metrics on Medium

Data Collection

  • Download and run scrape_medium_stats.py after replacing the USER and PASS variables with your Google login (your Medium account must be linked with Google)
  • If you want to tweak things or alter the code for alternate logins (Facebook, Twitter, etc.), then walk through the Medium Stats Data Collection jupyter notebook
  • Once you've collected your data, it will be placed in a file named mystats.csv (similar to mine in this repo).

Data Analysis

  • Check out my analysis in Medium Stats Data Analysis or perform your own!
  • An example of my data is available in mystats.csv as a starter dataset, feel free to share and explore.

Notes

It's worth noting that this type of analysis should be available to all writers, not just those that are data science practioners. Data analysis should be democratized for writers and content creators. Even with my ~30 post sample size, I was able to walk away with some interesting insights:

  • 2 out of my 30+ posts make up over 70% of my total lifetime views
  • Read Ratio and Read Time appear to be strongly correlated
  • Publication choice matters for engagement stats like Fan Ratio
  • Read Ratio and Fan Ratio correlated - strong posts do both well

This analysis is just from using the fraction of data available to users on the Medium Stats page. Imagine if we had more of our data and information at our disposal; if writers were empowered to use Medium Stats for improving their work and understanding how readers perceive it rather than boosting their ego with simple vanity stats. It's no small task, but I believe it can be done.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].