what are the topics pulled from Reddit?
training data has posts from politics, business, science and other popular topics; the trained model is applied to millions of unannotated posts on all of Reddit
We explore linguistic and behavioral features of dogmatism in social media and construct statistical models that can identify dogmatic comments. Our model is based on a corpus of Reddit posts, collected across a diverse set of conversational topics and annotated via paid crowdsourcing. We operationalize key aspects of dogmatism described by existing psychology theories (such as over-confidence), finding they have predictive power. We also find evidence for new signals of dogmatism, such as the tendency of dogmatic posts to refrain from signaling cognitive processes. When we use our predictive model to analyze millions of other Reddit posts, we find evidence that suggests dogmatism is a deeper personality trait, present for dogmatic users across many different domains, and that users who engage on dogmatic comments tend to show increases in dogmatic posts themselves.
“I'm supposed to trust the opinion of a MS minion? The people that produced Windows ME, Vista and 8? They don't even understand people, yet they think they can predict the behavior of new, self-guiding AI?” –anonymous “I think an AI would make it easier for Patients to confide their information because by nature, a robot cannot judge them. Win-win? :D”' –anonymous Dogmatism describes the tendency to lay down opinions as incontrovertibly true, without respect for conflicting evidence or the opinions of others BIBREF0 . Which user is more dogmatic in the examples above? This question is simple for humans. Phrases like “they think” and “they don't even understand,” suggest an intractability of opinion, while “I think” and “win-win?” suggest the opposite. Can we train computers to draw similar distinctions? Work in psychology has called out many aspects of dogmatism that can be modeled computationally via natural language, such as over-confidence and strong emotions BIBREF1 . We present a statistical model of dogmatism that addresses two complementary goals. First, we validate psychological theories by examining the predictive power of feature sets that guide the model's predictions. For example, do linguistic signals of certainty help to predict a post is dogmatic, as theory would suggest? Second, we apply our model to answer four questions: R1: What kinds of topics (e.g., guns, LGBT) attract the highest levels of dogmatism? R2: How do dogmatic beliefs cluster? R3: How does dogmatism influence a conversation on social media? R4: How do other user behaviors (e.g., frequency and breadth of posts) relate to dogmatism? We train a predictive model to classify dogmatic posts from Reddit, one of the most popular discussion communities on the web. Posts on Reddit capture discussion and debate across a diverse set of domains and topics – users talk about everything from climate change and abortion, to world news and relationship advice, to the future of artificial intelligence. As a prerequisite to training our model, we have created a corpus of 5,000 Reddit posts annotated with levels of dogmatism, which we are releasing to share with other researchers. Using the model, we operationalize key domain-independent aspects of psychological theories of dogmatism drawn from the literature. We find these features have predictive power that largely supports the underlying theory. For example, posts that use less confident language tend to be less dogmatic. We also discover evidence for new attributes of dogmatism. For example, dogmatic posts tend not to verbalize cognition, through terms such as “I think,” “possibly,” or “might be.” Our model is trained on only 5,000 annotated posts, but once trained, we use it to analyze millions of other Reddit posts to answer our research questions. We find a diverse set of topics are colored by dogmatic language (e.g., people are dogmatic about religion, but also about LGBT issues). Further, we find some evidence for dogmatism as a deeper personality trait – people who are strongly dogmatic about one topic are more likely to express dogmatic views about others as well. Finally, in conversation, we discover that one user's dogmatism tends to bring out dogmatism in their conversational partner, forming a vicious cycle.