RoleNet: Movie Analysis from the Perspective of Social Networks

Weng, Chung-Yi; Chu, Wei-Ta; Wu, Ja‐Ling

doi:10.1109/tmm.2008.2009684

Cited by 149 publications

(133 citation statements)

References 34 publications

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“…Movie summarization is a special type of video summarization which poses many challenges due to the large variety of film styles and genres. A few recent studies (Weng et al, 2009;Lin et al, 2013) have used concepts from social network analysis to identify lead roles and role communities in order to segment movies into scenes (containing one or more shots) and create more informative summaries. A surprising fact about this line of work is that it does not exploit the movie script in any way.…”

Section: Related Workmentioning

confidence: 99%

Movie Script Summarization as Graph-based Scene Extraction

Gorinski¹,

Lapata²

2015

Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Langua

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In this paper we study the task of movie script summarization, which we argue could enhance script browsing, give readers a rough idea of the script's plotline, and speed up reading time. We formalize the process of generating a shorter version of a screenplay as the task of finding an optimal chain of scenes. We develop a graph-based model that selects a chain by jointly optimizing its logical progression, diversity, and importance. Human evaluation based on a question-answering task shows that our model produces summaries which are more informative compared to competitive baselines.

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Section: Related Workmentioning

confidence: 99%

Movie Script Summarization as Graph-based Scene Extraction

Gorinski¹,

Lapata²

2015

Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Langua

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“…There have been studies on role recognition in groups. This research is split into recognition tasks of formal [13] or informal roles [14], [15]. In [16], a multimodal analysis is conducted for inferring emergent leadership in small groups.…”

Section: Computational Multimodal Analysis For Group Meetingsmentioning

confidence: 99%

Predicting Performance of Collaborative Storytelling Using Multimodal Analysis

Okada

Hang

Nitta

2016

IEICE Trans. Inf. & Syst.

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SUMMARYThis study focuses on modeling the storytelling performance of the participants in a group conversation. Storytelling performance is one of the fundamental communication techniques for providing information and entertainment effectively to a listener. We present a multimodal analysis of the storytelling performance in a group conversation, as evaluated by external observers. A new multimodal data corpus is collected through this group storytelling task, which includes the participants' performance scores. We extract multimodal (verbal and nonverbal) features regarding storytellers and listeners from a manual description of spoken dialog and from various nonverbal patterns, including each participant's speaking turn, utterance prosody, head gesture, hand gesture, and head direction. We also extract multimodal co-occurrence features, such as head gestures, and interaction features, such as storyteller utterance overlapped with listener's backchannel. In the experiment, we modeled the relationship between the performance indices and the multimodal features using machine-learning techniques. Experimental results show that the highest accuracy (R 2 ) is 0.299 for the total storytelling performance (sum of indices scores) obtained with a combination of verbal and nonverbal features in a regression task.

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“…They proposed a grammar to parse screenplays and show results for aligning one screenplay with its video. Weng et al (2009) motivated the need for screenplay parsing from a social network analysis perspective. They proposed a set of operations on social networks extracted from movies and television shows in order to find what they called hidden semantic information.…”

Section: Literature Surveymentioning

confidence: 99%

“…We extract a network from our test movie screenplay (Silver Linings Playbook) by using the tags of the screenplay as follows (Weng et al, 2009): we connect all characters having a dialogue with each other in a scene with links. Nodes in this network are characters, and links between two characters signal their participation in the same scene.…”

Section: Performance On the Test Setmentioning

confidence: 99%

“…Movies, which can be seen as visual approximations of unstructured literary works, contain rich social networks formed by interactions between characters. There has been some effort in the past to extract social networks from movies (Weng et al, 2006;Weng et al, 2007;Weng et al, 2009;Gil et al, 2011). However, these approaches are primarily regular expression based with no evaluation of how well they work.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Proceedings of the 3rd Workshop on Computational Linguistics for Literature (CLFL)

Feldman¹,

Kazantseva²,

Śzpakowicz³

2014

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ii Preface Welcome to the third edition of the workshop on Computational Linguistics for Literature. What started out two years ago as a small affair with an unorthodox title seems to be shaping into a modestly sized but vibrant research community.Thanks to the effort of the authors and the program committee, April 27, 2014 promises to be an interesting day. This year's workshop boasts the rich pickings of papers focussed on creating character representations from text and on applications of such representations. Agarwal et al. present a system for extracting social networks from movie scripts. Coll Ardanuy and Sporleder propose a method of finding similar novels using social networks as the underlying representation. Bullard and Alm work on identifying social information about characters from dialogues in a corpus of plays. Taking this a step further, Iosif and Mishra describe an integrated system for identifying and classifying characters in children's stories based on direct and indirect speech.Taking a complementary point of view, the position paper by Levison and Lessard builds upon their previous work and proposes a graph-based representation for the temporal structure of narratives. The paper by Zemánek and Milička describes a diachronic study of Arabic literature, tracing the influence of certain treatises across centuries.In the categories all of their own are two more papers. Davis and Mohammad break new ground with a paper on generating music from literature; you can listen to a one-minute musical summary of a novel. Mike Kestemont presents a position paper on authorship attribution, a topic which was quite popular in the 2012 and 2013 editions of the workshop.Last but by no means least, we are delighted to have two invited speakers this year. An artist and researcher María Mencía from Kingston University in London will talk about electronic poetry. Jan Christoph Meister from University of Hamburg will tell us about the connections between narratology and computation.We look forward to seeing you in Göteborg. Language-Art Digital Poetics: An exploration of digital textualities in the production of artistic research María Mencía Faculty of Arts and Social Sciences Kingston University AbstractAs an academic and an artist my practice-based research is at the intersection of language, art and digital technology. It explores the area of the in-between, the visual, the aural and the semantic. I am always interested in experimenting with the digital medium with the aim of engaging the reader/viewer/user in an experience of shifting 'in' and 'out' of language. This involves looking 'at' and looking 'through' transparent and abstract textualities and linguistic soundscapes. It draws from avant-garde poetics remediating concepts of reading and writing, exploring digital media grammars (voice activation, use of webcam, use of mouse, acts of revealing, triggering, cut and paste, dragging) for interactivity, aesthetics, engagement and meaning production. It is trans-disciplinary, bringing together different cultu...

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RoleNet: Movie Analysis from the Perspective of Social Networks

Cited by 149 publications

References 34 publications

Movie Script Summarization as Graph-based Scene Extraction

Movie Script Summarization as Graph-based Scene Extraction

Predicting Performance of Collaborative Storytelling Using Multimodal Analysis

Proceedings of the 3rd Workshop on Computational Linguistics for Literature (CLFL)

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