데이터셋 탐색

The Reddit dataset is a graph dataset from Reddit posts made in the month of September, 2014. The node label in this case is the community, or “subreddit”, that a post belongs to. 50 large communities have been sampled to build a post-to-post graph, connecting posts if the same user comments on both. In total this dataset contains 232,965 posts with an average degree of 492. The first 20 days are used for training and the remaining days for testing (with 30% used for validation). For features, off-the-shelf 300-dimensional GloVe CommonCrawl word vectors are used. Source: https://arxiv.org/pdf/1706.02216.pdf Image Source: https://minimaxir.com/2016/05/reddit-graph/

REDDIT-BINARY consists of graphs corresponding to online discussions on Reddit. In each graph, nodes represent users, and there is an edge between them if at least one of them respond to the other’s comment. There are four popular subreddits, namely, IAmA, AskReddit, TrollXChromosomes, and atheism. IAmA and AskReddit are two question/answer based subreddits, and TrollXChromosomes and atheism are two discussion-based subreddits. A graph is labeled according to whether it belongs to a question/answer-based community or a discussion-based community. Source: A simple yet effective baseline for non-attributed graph classification

Reddit-5K is a relational dataset extracted from Reddit.

Reddit TIFU dataset is a newly collected Reddit dataset, where TIFU denotes the name of /r/tifu subbreddit. There are 122,933 text-summary pairs in total. Source: https://github.com/ctr4si/MMN

Pushshift makes available all the submissions and comments posted on Reddit between June 2005 and April 2019. The dataset consists of 651,778,198 submissions and 5,601,331,385 comments posted on 2,888,885 subreddits.

Reddit12k contains 11929 graphs each corresponding to an online discussion thread where nodes represent users, and an edge represents the fact that one of the two users responded to the comment of the other user. There is 1 of 11 graph labels associated with each of these 11929 discussion graphs, representing the category of the community. Source: Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity

Moral Foundations Reddit Corpus (MFRC) is a collection of 16,123 Reddit comments that have been curated from 12 distinct subreddits, hand-annotated by at least three trained annotators for 8 categories of moral sentiment (i.e., Care, Proportionality, Equality, Purity, Authority, Loyalty, Thin Morality, Implicit/Explicit Morality) based on the updated Moral Foundations Theory (MFT) framework. Source: The Moral Foundations Reddit Corpus Image Source: https://arxiv.org/pdf/2208.05545v2.pdf

Reddit Corpus is part of a repository of conversational datasets consisting of hundreds of millions of examples, and a standardised evaluation procedure for conversational response selection models using '1-of-100 accuracy'. The Reddit Corpus contains 726 million multi-turn dialogues from the Reddit board. Source: conversational-datasets Image source: Henderson et al.

Reddit Conversation Corpus (RCC) consists of conversations, scraped from Reddit, for a 20 month period from November 2016 until August 2018. To ensure the quality and diversity of topics, 95 subreddits are selected from which conversations are collected. In total, RCC contains 9.2 million 3-turn conversations.

We analyze social media posts to tease out what makes a post inspiring and what topics are inspiring. We release a dataset of 5,800 inspiring and 5,800 non-inspiring English-language public post unique ids collected from a dump of Reddit public posts made available by a third party and use linguistic heuristics to automatically detect which social media English-language posts are inspiring.

Prepositions Annotated with Supersense Tags in Reddit International English (PASTRIE) is a new corpus containing manually annotated preposition supersenses of English data from presumed speakers of four L1s: English, French, German, and Spanish

RTC is a benchmark corpus of social media comments sampled over three years. The corpus consists of 36.36m unlabelled comments for adaptation and evaluation on an upstream masked language modelling task as well as 0.9m labelled comments for finetuning and evaluation on a downstream document classification task. The Reddit Time Corpus (RTC) covers three years between March 2017 and February 2020 and is split into 36 evenly-sized monthly subsets based on comment timestamps. RTC is sampled from the Pushshift Reddit dataset.

The C-SSRS dataset contains 500 Reddit posts from the subreddit r/depression. These posts are labeled by psychologists on a five point scale according to guidelines established in the Columbia Suicide Severity Rating Scale, which progress according to severity of depression. As this dataset is clinically verified and labeled, it is an adequate dataset to validate the label correction method, especially since it is from the same domain of mental health. Source: Deep Learning for Suicide and Depression Identification with Unsupervised Label Correction Paper: Knowledge-aware Assessment of Severity of Suicide Risk for Early Intervention

Articles originating from subreddits with explicitly stated ideologies are categorized into three groups: 72,488 articles in the Liberal class, 79,573 articles in the Conservative class, and 225,083 articles in the Restricted class. Conversely, articles from subreddits lacking a clearly defined ideology, including those with implicit or explicit ideologies, are merged to form a holdout dataset comprising 922,522 articles. Part 1 https://data.mendeley.com/datasets/2tdr9sjd83/3 Part 2 https://data.mendeley.com/datasets/dxpp5983yb/1 Part 3 https://data.mendeley.com/datasets/f7knr8r94w/1

A diverse dataset of written code-switched productions, curated from topical threads of multiple bilingual communities on the Reddit discussion platform, and explore questions that were mainly addressed in the context of spoken language thus far. Source: CodeSwitch-Reddit: Exploration of Written Multilingual Discourse in Online Discussion Forums

Dataset Summary New dataset introduced in Parameter-Efficient Legal Domain Adaptation (Li et al., 2022) from the Legal Advice Reddit community (known as "/r/legaldvice"), sourcing the Reddit posts from the Pushshift Reddit dataset. The dataset maps the text and title of each legal question posted into one of eleven classes, based on the original Reddit post's "flair" (i.e., tag). Questions are typically informal and use non-legal-specific language. Per the Legal Advice Reddit rules, posts must be about actual personal circumstances or situations. We limit the number of labels to the top eleven classes and remove the other samples from the dataset. ## Citation Information @inproceedings{li-etal-2022-parameter, title = "Parameter-Efficient Legal Domain Adaptation", author = "Li, Jonathan and Bhambhoria, Rohan and Zhu, Xiaodan", booktitle = "Proceedings of the Natural Legal Language Processing Workshop 2022", month = dec, year = "2022", address = "Abu Dhabi, United Arab Emirates (Hybrid)", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2022.nllp-1.10", pages = "119--129", }

The Reddit Photo Critique Dataset (RPCD) contains tuples of image and photo critiques. RPCD consists of 74K images and 220K comments and is collected from a Reddit community used by hobbyists and professional photographers to improve their photography skills by leveraging constructive community feedback. The proposed dataset differs from previous aesthetics datasets mainly in three aspects, namely * the large scale of the dataset and the extension of the comments criticizing different aspects of the image; * it contains mostly UltraHD images; * it can easily be extended to new data as it is collected through an automatic pipeline.

Reddit Engagement Dataset (RED), a distant-supervision set, with 80k single-turn conversations. RED is sourced from Reddit, sampling from 43 popular subreddits, and processed from a total of 5 million posts, filtering out data that was either non-conversational, toxic, or posts not possible to ascertain popularity. Source: EnDex: Evaluation of Dialogue Engagingness at Scale Image Source: https://arxiv.org/pdf/2210.12362v1.pdf

Dataset with articles posted in the r/Liberal and r/Conservative subreddits. In total, we collected a corpus of 226,010 articles. We have collected news articles to understand political expression through the shared news articles.

This is a dataset of over 40K Reddit comments removed by moderators according to the specific type of macro norm being violated.

This dataset comprises 77,175 Reddit posts from 115 subreddit forums, annotated for the presence of 15 topics related to eating disorders and dieting. The dataset includes labels and scores on all 77,175 Reddit posts, determined by 5 Large Language Models: GPT-4o, Llama-3.1-8B-Instruct, Qwen2.5-7B-Instruct, Mistral-7B-Instruct-v0.3, Vicuna-7b-v1.5, as well as by the ensemble of the four open-source LLMs. The dataset also includes a subset of 1,080 human-annotated posts for evaluation.

https://arxiv.org/abs/2503.15222

The Reddit Climate Change Dataset is a dataset of 620K Reddit posts and 4.6M comments - all mentions of the terms "climate" and "change" until 2022-09-01 across the entire Reddit social network. Both were procured with SocialGrep's export feature and released as part of SocialGrep Reddit datasets. The posts are labeled with their subreddit, title, creation date, domain, selftext, and score. The comments are labeled with their subreddit, body, creation date, sentiment (calculated for you using a VADER pipeline), and score.

This dataset is made of 6366 threads collected from the r/AmITheAsshole community on Reddit. The dataset contains a total of 6,372,251 comments. The collected threads constitute the “top” submissions — those having the highest score, measured as the difference between upvotes and downvotes of a post. We downloaded them using PRAW, running 10 different queries across various temporal scopes, and then cleaning the obtained dataset by removing duplicated threads. Please refer to the paper, specifically to Table 3, for more details about the dataset.

The Reddit COVID Dataset is a dataset of 4.51M Reddit posts and 17.8M comments - all mentions of COVID until 2021-10-25 across the entire Reddit social network. Both were procured with SocialGrep's export feature and released as part of SocialGrep Reddit datasets. The posts are labeled with their subreddit, title, creation date, domain, selftext, and score. The comments are labeled with their subreddit, body, creation date, sentiment (calculated for you using a VADER pipeline), and score.