Description

## Context/background Discourse acts are the different types of things you can do in a conversation, like agreeing, disagreeing or elaborating. This dataset contains annotations of the discourse acts of different Twitter comments. The discourse acts labeled here are “coarse” in the sense that they’re labelled broadly (for the whole Reddit comment) rather than for individual sentences or phrases, not in the sense of being vulgar. The discourse act of each post has been annotated by multiple annotators. ## Content A large corpus of discourse annotations and relations on ~10K forum threads. Please refer to the following paper for an in depth analysis and explanation of the data: [*Characterizing Online Discussion Using Coarse Discourse Sequences (ICWSM '17)*](https://research.google.com/pubs/pub46055.html). ## Explanation of fields Thread fields * URL - reddit URL of the thread * title - title of the thread, as written by the first poster * is_self_post - True if the first post in the thread is a self-post (text addressed to the reddit community as opposed to an external link) * subreddit - the subreddit of the thread * posts - a list of all posts in the thread Post fields * id - post ID, reddit ID of the current post * in_reply_to - parent ID, reddit ID of the parent post, or the post that the current post is in reply to * post_depth - the number of replies the current post is from the initial post * is_first_post - True if the current post is the initial post * annotations - a list of all annotations made to this post (see below) * majority_type - the majority annotated type, if there is a majority type between the annotators, when considering only the main_type field * majority_link - the majority annotated link, if there is a majority link between the annotators Annotation fields * annotator - an unique ID for the annotator * main_type - the main discourse act that describes this post * secondary_type - if a post contains more than one discourse act in sequence, this is the second discourse act in the post * link_to_post - the post that this post is linked to ## Data sampling and pre-processing Selecting Reddit threads This data was randomly sampled from the full Reddit dataset starting from its inception to the end of May 2016, which is made available publicly as a dump on [Google BigQuery](https://bigquery.cloud.google.com/table/fh-bigquery:reddit_comments.2016_05). This dataset was subsampled from the larger dataset and does not include posts with fewer than two comments, not in English, which contain pornographic material or from Subreddits focused on trading. Further, the number of replies to a single thread was limited to 40. Annotation Three annotators were assigned to each thread and were instructed to annotate each comment in the thread with its discourse act (main_type) as well as the relation of each comment to a prior comment (link_to_post), if it existed. Annotators were instructed to consider the content at the comment level as opposed to sentence or paragraph level to make the task simpler. ## Authors **Amy X. Zhang**, MIT CSAIL, Cambridge, MA, USA. axz@mit.edu **Ka Wong**, Google, Mountain View, CA, USA. kawong@google.com **Bryan Culbertson**, Calthorpe Analytics, Berkeley, CA, USA. bryan.culbertson@gmail.com **Praveen Paritosh**, Google, Mountain View, CA, USA. pkp@google.com ## Citation Guidelines If you are using this data towards a research publication, please cite the following paper. Amy X. Zhang, Bryan Culbertson, Praveen Paritosh. *Characterizing Online Discussion Using Coarse Discourse Sequences. In Proceedings of the International AAAI Conference on Weblogs and Social Media (ICWSM '17)*. Montreal, Canada. 2017. Bibtex: @inproceedings{coarsediscourse, title={Characterizing Online Discussion Using Coarse Discourse Sequences}, author={Zhang, Amy X. and Culbertson, Bryan and Paritosh, Praveen}, booktitle={Proceedings of the 11th International AAAI Conference on Weblogs and Social Media}, series={ICWSM '17}, year={2017}, location = {Montreal, Canada} } ## License CC-by ## Inspiration * Can you visualize which discourse acts are used to in replies to each kind of discourse act? * Are threads more likely to be made up of a single type of discourse act or multiple discourse acts? * Are certain discourse acts more closely associated with specific subreddits?