1. A computer-implemented method for automatically augmenting online content with contextually relevant comments, the method comprising: receiving, by a computer from a network server that hosts an online content provider, online content from the online content provider; receiving, by the computer from the online content provider, user-entered comments associated with the online content: classifying the comments, by a trained machine learning model on the computer, as either chit-chat if the comment corresponds to training data characterized as meaningless, unhelpful, or unimportant, or informative if the comment corresponds to training data characterized as containing valuable information: for each comment classified as informative: determining, by the computer, a portion of the online content to which the comment is most relevant, wherein the determining further comprises: converting the online content data to text; assigning, by the computer, scores to segments of the text indicating a relevance of the comment to each segment, and identifying a segment with the highest score; and associating, by the computer, the comment with a position in the online content that corresponds to the determined portion of the online content; selecting, by the computer, a subset of the informative comments for presentation, based on a predefined criteria, wherein the predefined criteria comprises a selection based on one or more of informative comments having a score exceeding a predefined threshold, recentness, randomness, a known or inferred profile of a user, a probabilistic basis according to a predefined distribution, or in real time, concurrently with user interaction with the online content; converting the selected subset of the informative commands from text to a format suitable for presentation with the online content data; and annotating, by the computer, the online content with the selected subset of informative comments at the positions in the online content associated with respective comments in the subset of informative comments.
1. A computer-implemented method for automatically augmenting online content with contextually relevant comments, the method comprising: receiving, by a computer from a network server that hosts an online content provider, online content from the online content provider; receiving, by the computer from the online content provider, user-entered comments associated with the online content: classifying the comments, by a trained machine learning model on the computer, as either chit-chat if the comment corresponds to training data characterized as meaningless, unhelpful, or unimportant, or informative if the comment corresponds to training data characterized as containing valuable information: for each comment classified as informative: determining, by the computer, a portion of the online content to which the comment is most relevant, wherein the determining further comprises: converting the online content data to text; assigning, by the computer, scores to segments of the text indicating a relevance of the comment to each segment, and identifying a segment with the highest score; and associating, by the computer, the comment with a position in the online content that corresponds to the determined portion of the online content; selecting, by the computer, a subset of the informative comments for presentation, based on a predefined criteria, wherein the predefined criteria comprises a selection based on one or more of informative comments having a score exceeding a predefined threshold, recentness, randomness, a known or inferred profile of a user, a probabilistic basis according to a predefined distribution, or in real time, concurrently with user interaction with the online content; converting the selected subset of the informative commands from text to a format suitable for presentation with the online content data; and annotating, by the computer, the online content with the selected subset of informative comments at the positions in the online content associated with respective comments in the subset of informative comments. 2. A method in accordance with claim 1 , wherein the online content is audio or video data, and the method further comprises: converting, by the computer, speech in the online content to text; and wherein determining comprises determining, by the computer, a portion of the text to which the comment is most relevant.