Examples ======== An index of useful examples to help you interactively explore ConvoKit's features. Be sure to take a look at the `introductory tutorial `_ before exploring these examples! General ConvoKit usage (starting resource) ------------------------------------------ - `Introductory tutorial to ConvoKit `_ - Creating a ConvoKit Corpus from existing data: - `Converting custom dataset into ConvoKit format corpus `_ - `Constructing ConvoKit format corpus from pandas dataframe `_ - `Using vector data in ConvoKit `_ - `Pre-processing text, e.g. computing dependency parses `_ Intermediate corpus functionality --------------------------------- - `Merging two different Corpora (even when there are overlaps or conflicts in Corpus data) `_ - `Partially loading utterances from an included dataset `_ Classifier ------------ - `Extracting bag-of-Words vectors from utterances and using them in various classification tasks `_ - `Using common politeness strategies for various predictive tasks `_ Coordination ------------ - `Exploring the balance of power in Wikipedia and the US Supreme Court `_ Expected Conversational Context Framework ----------------------------------------- - `deriving question types and other characterizations in British parliamentary question periods `_ - exploration of Switchboard dialog acts corpus `using ExpectedContextModelTransformer `_, and `using DualContextWrapper `_ - `examining Wikipedia talk page discussions `_ - `computing the orientation of justice utterances in the US Supreme Court `_ Fighting Words -------------- - `Examining the Fighting Words of mixed-gender vs. single-gender conversations in movies `_ - `Examining the Fighting Words of r/atheism vs r/Christianity `_ Forecaster ---------- - `CRAFT forecasting of conversational derailment `_ - `Forecasting of conversational derailment using a cumulative bag-of-words model `_ Hyperconvo ---------- - `Categorizing and analyzing subreddits using Hyperconvo features `_ - `Using Hyperconvo features to predict conversation growth on Reddit in a paired setting `_ .. Prompt Types .. ------------ .. - `Exploring common types of questioning in the UK Parliament `_ .. - `Using prompt types and politeness strategies to predict Wikipedia conversations going awry `_ Politeness Strategies --------------------- - `Exploring common politeness strategies used in Stanford Politeness Corpus `_ - `Using politeness strategies to predict Wikipedia conversations gone awry `_ Ranker ------ - `Ranking users in r/Cornell by the number of comments they have made `_ Speaker Convo Diversity ----------------------- - `Speaker conversation attributes and diversity example on ChangeMyView `_