News Generation

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/

FakeNewsNet is collected from two fact-checking websites: GossipCop and PolitiFact containing news contents with labels annotated by professional journalists and experts, along with social context information. Source: Leveraging Multi-Source Weak Social Supervision for Early Detection of Fake News Image Source: https://arxiv.org/pdf/1809.01286.pdf

An open corpus of Scientific Research papers which has a representative sample from across scientific disciplines. This corpus not only includes the full text of the article, but also the metadata of the documents, along with the bibliographic information for each reference. Source: Elsevier OA CC-By Corpus

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

We present YTSeg, a topically and structurally diverse benchmark for the text segmentation task based on YouTube transcriptions. The dataset comprises 19,299 videos from 393 channels, amounting to 6,533 content hours. The topics are wide-ranging, covering domains such as science, lifestyle, politics, health, economy, and technology. The videos are from various types of content formats, such as podcasts, lectures, news, corporate events & promotional content, and, more broadly, videos from individual content creators. We refer to the paper for further information.

Ice Hockey News Dataset is a corpus of Finnish ice hockey news, edited to be suitable for training of end-to-end news generation methods, as well as demonstrate generation of text, which was judged by journalists to be relatively close to a viable product. Source: Template-free Data-to-Text Generation of Finnish Sports News

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.

A Filipino multi-modal language dataset for text+visual tasks. Consists of 351,755 Filipino news articles gathered from Filipino news outlets. Each entry contains: * body - Article text * title - Article title * website - Name of the news outlet * category - News category given by the news outlet * date - Date published * author - Article author * url - URL of the article * img_url - URL of the article image * img_path - Filename of the image in the dataset