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metadata
dataset_info:
  features:
    - name: subreddit
      dtype: string
    - name: post_id
      dtype: string
    - name: sentence_range
      dtype: string
    - name: text
      dtype: string
    - name: id
      dtype: int64
    - name: label
      dtype: int64
    - name: confidence
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    - name: social_timestamp
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    - name: social_karma
      dtype: int64
    - name: syntax_ari
      dtype: float64
    - name: lex_liwc_WC
      dtype: int64
    - name: lex_liwc_Analytic
      dtype: float64
    - name: lex_liwc_Clout
      dtype: float64
    - name: lex_liwc_Authentic
      dtype: float64
    - name: lex_liwc_Tone
      dtype: float64
    - name: lex_liwc_WPS
      dtype: float64
    - name: lex_liwc_Sixltr
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    - name: lex_liwc_Dic
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    - name: lex_liwc_function
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    - name: lex_liwc_pronoun
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    - name: lex_liwc_ppron
      dtype: float64
    - name: lex_liwc_i
      dtype: float64
    - name: lex_liwc_we
      dtype: float64
    - name: lex_liwc_you
      dtype: float64
    - name: lex_liwc_shehe
      dtype: float64
    - name: lex_liwc_they
      dtype: float64
    - name: lex_liwc_ipron
      dtype: float64
    - name: lex_liwc_article
      dtype: float64
    - name: lex_liwc_prep
      dtype: float64
    - name: lex_liwc_auxverb
      dtype: float64
    - name: lex_liwc_adverb
      dtype: float64
    - name: lex_liwc_conj
      dtype: float64
    - name: lex_liwc_negate
      dtype: float64
    - name: lex_liwc_verb
      dtype: float64
    - name: lex_liwc_adj
      dtype: float64
    - name: lex_liwc_compare
      dtype: float64
    - name: lex_liwc_interrog
      dtype: float64
    - name: lex_liwc_number
      dtype: float64
    - name: lex_liwc_quant
      dtype: float64
    - name: lex_liwc_affect
      dtype: float64
    - name: lex_liwc_posemo
      dtype: float64
    - name: lex_liwc_negemo
      dtype: float64
    - name: lex_liwc_anx
      dtype: float64
    - name: lex_liwc_anger
      dtype: float64
    - name: lex_liwc_sad
      dtype: float64
    - name: lex_liwc_social
      dtype: float64
    - name: lex_liwc_family
      dtype: float64
    - name: lex_liwc_friend
      dtype: float64
    - name: lex_liwc_female
      dtype: float64
    - name: lex_liwc_male
      dtype: float64
    - name: lex_liwc_cogproc
      dtype: float64
    - name: lex_liwc_insight
      dtype: float64
    - name: lex_liwc_cause
      dtype: float64
    - name: lex_liwc_discrep
      dtype: float64
    - name: lex_liwc_tentat
      dtype: float64
    - name: lex_liwc_certain
      dtype: float64
    - name: lex_liwc_differ
      dtype: float64
    - name: lex_liwc_percept
      dtype: float64
    - name: lex_liwc_see
      dtype: float64
    - name: lex_liwc_hear
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    - name: lex_liwc_feel
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    - name: lex_liwc_bio
      dtype: float64
    - name: lex_liwc_body
      dtype: float64
    - name: lex_liwc_health
      dtype: float64
    - name: lex_liwc_sexual
      dtype: float64
    - name: lex_liwc_ingest
      dtype: float64
    - name: lex_liwc_drives
      dtype: float64
    - name: lex_liwc_affiliation
      dtype: float64
    - name: lex_liwc_achieve
      dtype: float64
    - name: lex_liwc_power
      dtype: float64
    - name: lex_liwc_reward
      dtype: float64
    - name: lex_liwc_risk
      dtype: float64
    - name: lex_liwc_focuspast
      dtype: float64
    - name: lex_liwc_focuspresent
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    - name: lex_liwc_focusfuture
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    - name: lex_liwc_relativ
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    - name: lex_liwc_motion
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    - name: lex_liwc_space
      dtype: float64
    - name: lex_liwc_time
      dtype: float64
    - name: lex_liwc_work
      dtype: float64
    - name: lex_liwc_leisure
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    - name: lex_liwc_home
      dtype: float64
    - name: lex_liwc_money
      dtype: float64
    - name: lex_liwc_relig
      dtype: float64
    - name: lex_liwc_death
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    - name: lex_liwc_informal
      dtype: float64
    - name: lex_liwc_swear
      dtype: float64
    - name: lex_liwc_netspeak
      dtype: float64
    - name: lex_liwc_assent
      dtype: float64
    - name: lex_liwc_nonflu
      dtype: float64
    - name: lex_liwc_filler
      dtype: float64
    - name: lex_liwc_AllPunc
      dtype: float64
    - name: lex_liwc_Period
      dtype: float64
    - name: lex_liwc_Comma
      dtype: float64
    - name: lex_liwc_Colon
      dtype: float64
    - name: lex_liwc_SemiC
      dtype: float64
    - name: lex_liwc_QMark
      dtype: float64
    - name: lex_liwc_Exclam
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    - name: lex_liwc_Dash
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    - name: lex_liwc_Quote
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    - name: lex_liwc_Apostro
      dtype: float64
    - name: lex_liwc_Parenth
      dtype: float64
    - name: lex_liwc_OtherP
      dtype: float64
    - name: lex_dal_max_pleasantness
      dtype: float64
    - name: lex_dal_max_activation
      dtype: float64
    - name: lex_dal_max_imagery
      dtype: float64
    - name: lex_dal_min_pleasantness
      dtype: float64
    - name: lex_dal_min_activation
      dtype: float64
    - name: lex_dal_min_imagery
      dtype: float64
    - name: lex_dal_avg_activation
      dtype: float64
    - name: lex_dal_avg_imagery
      dtype: float64
    - name: lex_dal_avg_pleasantness
      dtype: float64
    - name: social_upvote_ratio
      dtype: float64
    - name: social_num_comments
      dtype: int64
    - name: syntax_fk_grade
      dtype: float64
    - name: sentiment
      dtype: float64
  splits:
    - name: train
      num_bytes: 3929762
      num_examples: 2838
    - name: test
      num_bytes: 988933
      num_examples: 715
  download_size: 2297873
  dataset_size: 4918695
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
tags:
  - stress
  - social-media
  - reddit
pretty_name: 'Dreaddit: A Reddit Dataset for Stress Analysis in Social Media'
size_categories:
  - 1K<n<10K
language:
  - en

Dreaddit: A Reddit Dataset for Stress Analysis in Social Media

Consists of 190K posts from five different categories of Reddit communities.

Citation

@inproceedings{turcan-mckeown-2019-dreaddit,
    title = "{D}readdit: A {R}eddit Dataset for Stress Analysis in Social Media",
    author = "Turcan, Elsbeth  and
      McKeown, Kathy",
    editor = "Holderness, Eben  and
      Jimeno Yepes, Antonio  and
      Lavelli, Alberto  and
      Minard, Anne-Lyse  and
      Pustejovsky, James  and
      Rinaldi, Fabio",
    booktitle = "Proceedings of the Tenth International Workshop on Health Text Mining and Information Analysis (LOUHI 2019)",
    month = nov,
    year = "2019",
    address = "Hong Kong",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/D19-6213/",
    doi = "10.18653/v1/D19-6213",
    pages = "97--107",
    abstract = "Stress is a nigh-universal human experience, particularly in the online world. While stress can be a motivator, too much stress is associated with many negative health outcomes, making its identification useful across a range of domains. However, existing computational research typically only studies stress in domains such as speech, or in short genres such as Twitter. We present Dreaddit, a new text corpus of lengthy multi-domain social media data for the identification of stress. Our dataset consists of 190K posts from five different categories of Reddit communities; we additionally label 3.5K total segments taken from 3K posts using Amazon Mechanical Turk. We present preliminary supervised learning methods for identifying stress, both neural and traditional, and analyze the complexity and diversity of the data and characteristics of each category."
}