TY - GEN
T1 - Issue-focused documentaries versus other films
T2 - 27th ACM Conference on Hypertext and Social Media, HT 2016
AU - Jiang, Ming
AU - Diesner, Jana
PY - 2016/7/10
Y1 - 2016/7/10
N2 - User-authored reviews offer a window into micro-level engagement with issue-focused documentary films, which is a critical yet insufficiently understood topic in media impact assessment. Based on our data, features, and supervised learning method, we find that ratings of non-documentary (feature film) reviews can be predicted with higher accuracy (73.67%, F1 score) than ratings of documentary reviews (68.05%). We also constructed a classifier that separates reviews of documentaries from reviews of feature films with an accuracy of 71.32%. However, as our goal with this paper is not to improve the accuracy of predicting the rating and type or genre of film reviews, but to advance our understanding of the perception of documentaries in comparison to feature films, we also identified commonalities and differences between these two types of films as well as between low versus high ratings. We find that in contrast to reviews of feature films, comments on documentaries are shorter but composed of longer sentences, are less emotional, contain less positive and more negative terms, are lexically more concise, and are more focused on verbs than on nouns and adjectives. Compared to low-rated reviews, comments with a high rating are shorter, are more emotional and contain more positive than negative sentiment, and have less question marks and more exclamation points. Overall, this work contributes to advancing our understanding of the impact of different types of information products on individual information consumers.
AB - User-authored reviews offer a window into micro-level engagement with issue-focused documentary films, which is a critical yet insufficiently understood topic in media impact assessment. Based on our data, features, and supervised learning method, we find that ratings of non-documentary (feature film) reviews can be predicted with higher accuracy (73.67%, F1 score) than ratings of documentary reviews (68.05%). We also constructed a classifier that separates reviews of documentaries from reviews of feature films with an accuracy of 71.32%. However, as our goal with this paper is not to improve the accuracy of predicting the rating and type or genre of film reviews, but to advance our understanding of the perception of documentaries in comparison to feature films, we also identified commonalities and differences between these two types of films as well as between low versus high ratings. We find that in contrast to reviews of feature films, comments on documentaries are shorter but composed of longer sentences, are less emotional, contain less positive and more negative terms, are lexically more concise, and are more focused on verbs than on nouns and adjectives. Compared to low-rated reviews, comments with a high rating are shorter, are more emotional and contain more positive than negative sentiment, and have less question marks and more exclamation points. Overall, this work contributes to advancing our understanding of the impact of different types of information products on individual information consumers.
KW - Documentary films
KW - Rating prediction
KW - Social impact
KW - Type prediction
UR - http://www.scopus.com/inward/record.url?scp=84980335329&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84980335329&partnerID=8YFLogxK
U2 - 10.1145/2914586.2914638
DO - 10.1145/2914586.2914638
M3 - Conference contribution
AN - SCOPUS:84980335329
T3 - HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media
SP - 225
EP - 230
BT - HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media
PB - Association for Computing Machinery, Inc
Y2 - 10 July 2016 through 13 July 2016
ER -