# EstMV2020 — Data

来源：https://www.kaggle.com/competitions/estmv2020/data

本地 Meta Kaggle 快照；不是本次实时页面。

# Dataset Description

This dataset summarizes a heterogeneous set of features about articles published by Mashable in a period of two years. The goal is to predict if the article is among the most popular ones based on sharing in social networks (coded by the variable "is_popular").

The articles were published by Mashable (www.mashable.com) and their content as the rights to reproduce it belongs to them. Hence, this dataset does not share the original content but some statistics associated with it. Acquisition date: January 8, 2015.

**File descriptions**

- train.csv - the training set

- test.csv - the test set

- sample_submission.csv - a sample submission file in the correct format

**Data fields**

n_tokens_title: Number of words in the title

n_tokens_content: Number of words in the content

n_unique_tokens: Rate of unique words in the content

n_non_stop_words: Rate of non-stop words in the content

n_non_stop_unique_tokens: Rate of unique non-stop words in the content

num_hrefs: Number of links

num_self_hrefs: Number of links to other articles published by Mashable

num_imgs: Number of images

num_videos: Number of videos

average_token_length: Average length of the words in the content

num_keywords: Number of keywords in the metadata

data_channel_is_lifestyle: Is data channel 'Lifestyle'?

data_channel_is_entertainment: Is data channel 'Entertainment'?

data_channel_is_bus: Is data channel 'Business'?

data_channel_is_socmed: Is data channel 'Social Media'?

data_channel_is_tech: Is data channel 'Tech'?

data_channel_is_world: Is data channel 'World'?

kw_min_min: Worst keyword (min. shares)

kw_max_min: Worst keyword (max. shares)

kw_avg_min: Worst keyword (avg. shares)

kw_min_max: Best keyword (min. shares)

kw_max_max: Best keyword (max. shares)

kw_avg_max: Best keyword (avg. shares)

kw_min_avg: Avg. keyword (min. shares)

kw_max_avg: Avg. keyword (max. shares)

kw_avg_avg: Avg. keyword (avg. shares)

self_reference_min_shares: Min. shares of referenced articles in Mashable

self_reference_max_shares: Max. shares of referenced articles in Mashable

self_reference_avg_sharess: Avg. shares of referenced articles in Mashable

weekday_is_monday: Was the article published on a Monday?

weekday_is_tuesday: Was the article published on a Tuesday?

weekday_is_wednesday: Was the article published on a Wednesday?

weekday_is_thursday: Was the article published on a Thursday?

weekday_is_friday: Was the article published on a Friday?

weekday_is_saturday: Was the article published on a Saturday?

weekday_is_sunday: Was the article published on a Sunday?

is_weekend: Was the article published on the weekend?

LDA_00: Closeness to LDA topic 0

LDA_01: Closeness to LDA topic 1

LDA_02: Closeness to LDA topic 2

LDA_03: Closeness to LDA topic 3

LDA_04: Closeness to LDA topic 4

global_subjectivity: Text subjectivity

global_sentiment_polarity: Text sentiment polarity

global_rate_positive_words: Rate of positive words in the content

global_rate_negative_words: Rate of negative words in the content

rate_positive_words: Rate of positive words among non-neutral tokens

rate_negative_words: Rate of negative words among non-neutral tokens

avg_positive_polarity: Avg. polarity of positive words

min_positive_polarity: Min. polarity of positive words

max_positive_polarity: Max. polarity of positive words

avg_negative_polarity: Avg. polarity of negative words

min_negative_polarity: Min. polarity of negative words

max_negative_polarity: Max. polarity of negative words

title_subjectivity: Title subjectivity

title_sentiment_polarity: Title polarity

abs_title_subjectivity: Absolute subjectivity level

abs_title_sentiment_polarity: Absolute polarity level

shares: Number of shares (target)