@InProceedings{10.1007/978-3-031-43129-6_5,
author="Chen, Kai and He, Zihao and Chang, Rong-Ching and May, Jonathan and Lerman, Kristina",
editor="Thomson, Robert and Al-khateeb, Samer and Burger, Annetta
and Park, Patrick
and A. Pyke, Aryn",
title="Anger Breeds Controversy: Analyzing Controversy and Emotions on Reddit",
booktitle="Social, Cultural, and Behavioral Modeling",
year="2023",
publisher="Springer Nature Switzerland",
address="Cham",
pages="44--53",
url = {https://arxiv.org/abs/2212.00339},
abstract="Emotions play an important role in interpersonal interactions and social conflict, yet their function in the development of controversy and disagreement in online conversations has not been fully explored. To address this gap, we study controversy on Reddit, a popular network of online discussion forums. We collect discussions from various topical forums and use emotion detection to recognize a range of emotions from text, including anger, fear, joy, admiration, etc. (Code and dataset are publicly available at https://github.com/ChenK7166/controversy-emotion). We find controversial comments express more anger and less admiration, joy, and optimism than non-controversial comments. Moreover, controversial comments affect emotions of downstream comments, resulting in a long-term increase in anger and a decrease in positive emotions. The magnitude and direction of emotional change differ by forum. Finally, we show that emotions help better predict which comments will become controversial. Understanding the dynamics of emotions in online discussions can help communities to manage conversations better.",
isbn="978-3-031-43129-6"
}

{"_id":"WfgJfDkqvo4JqNZbK","bibbaseid":"chen-he-chang-may-lerman-angerbreedscontroversyanalyzingcontroversyandemotionsonreddit-2023","author_short":["Chen, K.","He, Z.","Chang, R.","May, J.","Lerman, K."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"propositions":[],"lastnames":["Chen"],"firstnames":["Kai"],"suffixes":[]},{"propositions":[],"lastnames":["He"],"firstnames":["Zihao"],"suffixes":[]},{"propositions":[],"lastnames":["Chang"],"firstnames":["Rong-Ching"],"suffixes":[]},{"propositions":[],"lastnames":["May"],"firstnames":["Jonathan"],"suffixes":[]},{"propositions":[],"lastnames":["Lerman"],"firstnames":["Kristina"],"suffixes":[]}],"editor":[{"propositions":[],"lastnames":["Thomson"],"firstnames":["Robert"],"suffixes":[]},{"propositions":[],"lastnames":["Al-khateeb"],"firstnames":["Samer"],"suffixes":[]},{"propositions":[],"lastnames":["Burger"],"firstnames":["Annetta"],"suffixes":[]},{"propositions":[],"lastnames":["Park"],"firstnames":["Patrick"],"suffixes":[]},{"propositions":[],"lastnames":["A.","Pyke"],"firstnames":["Aryn"],"suffixes":[]}],"title":"Anger Breeds Controversy: Analyzing Controversy and¬†Emotions on¬†Reddit","booktitle":"Social, Cultural, and Behavioral Modeling","year":"2023","publisher":"Springer Nature Switzerland","address":"Cham","pages":"44–53","url":"https://arxiv.org/abs/2212.00339","abstract":"Emotions play an important role in interpersonal interactions and social conflict, yet their function in the development of controversy and disagreement in online conversations has not been fully explored. To address this gap, we study controversy on Reddit, a popular network of online discussion forums. We collect discussions from various topical forums and use emotion detection to recognize a range of emotions from text, including anger, fear, joy, admiration, etc. (Code and dataset are publicly available at https://github.com/ChenK7166/controversy-emotion). We find controversial comments express more anger and less admiration, joy, and optimism than non-controversial comments. Moreover, controversial comments affect emotions of downstream comments, resulting in a long-term increase in anger and a decrease in positive emotions. The magnitude and direction of emotional change differ by forum. Finally, we show that emotions help better predict which comments will become controversial. Understanding the dynamics of emotions in online discussions can help communities to manage conversations better.","isbn":"978-3-031-43129-6","bibtex":"@InProceedings{10.1007/978-3-031-43129-6_5,\nauthor=\"Chen, Kai and He, Zihao and Chang, Rong-Ching and May, Jonathan and Lerman, Kristina\",\neditor=\"Thomson, Robert and Al-khateeb, Samer and Burger, Annetta\nand Park, Patrick\nand A. Pyke, Aryn\",\ntitle=\"Anger Breeds Controversy: Analyzing Controversy and¬†Emotions on¬†Reddit\",\nbooktitle=\"Social, Cultural, and Behavioral Modeling\",\nyear=\"2023\",\npublisher=\"Springer Nature Switzerland\",\naddress=\"Cham\",\npages=\"44--53\",\nurl = {https://arxiv.org/abs/2212.00339},\nabstract=\"Emotions play an important role in interpersonal interactions and social conflict, yet their function in the development of controversy and disagreement in online conversations has not been fully explored. To address this gap, we study controversy on Reddit, a popular network of online discussion forums. We collect discussions from various topical forums and use emotion detection to recognize a range of emotions from text, including anger, fear, joy, admiration, etc. (Code and dataset are publicly available at https://github.com/ChenK7166/controversy-emotion). We find controversial comments express more anger and less admiration, joy, and optimism than non-controversial comments. Moreover, controversial comments affect emotions of downstream comments, resulting in a long-term increase in anger and a decrease in positive emotions. The magnitude and direction of emotional change differ by forum. Finally, we show that emotions help better predict which comments will become controversial. 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