VlogSense: Conversational behavior and social attention in YouTube

Authors:
Joan-Isaac Biel;Daniel Gatica-Perez
Affiliations:
Idiap Research Institute and Ecole Polytechnique Fédérale de Lausanne (EPFL), Martigny, Switzerland;Idiap Research Institute and Ecole Polytechnique Fédérale de Lausanne (EPFL), Martigny, Switzerland
Venue:
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) - Special section on ACM multimedia 2010 best paper candidates, and issue on social media
Year:
2011

Citing 20
Cited 2

Robust Real-Time Face Detection

International Journal of Computer Vision
Automatic detection of group functional roles in face to face interactions

Proceedings of the 8th international conference on Multimodal interfaces
Exploring social dynamics in online media sharing

Proceedings of the 16th international conference on World Wide Web
I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system

Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Measurement and analysis of online social networks

Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Word usage and posting behaviors: modeling blogs with unobtrusive data collection methods

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Honest Signals: How They Shape Our World

Honest Signals: How They Shape Our World
Predicting two facets of social verticality in meetings from five-minute time slices and nonverbal cues

ICMI '08 Proceedings of the 10th international conference on Multimodal interfaces
Investigating automatic dominance estimation in groups from visual attention and speaking activity

ICMI '08 Proceedings of the 10th international conference on Multimodal interfaces
Remote conversations: the effects of mediating talk with technology

Human-Computer Interaction
Broadcast yourself on YouTube: really?

HCC '08 Proceedings of the 3rd ACM international workshop on Human-centered computing
More than face-to-face: empathy effects of video framing

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
YouTube and intergenerational communication: the case of Geriatric1927

Universal Access in the Information Society
Image, appearance and vanity in the use of media spaces and video conference systems

Proceedings of the ACM 2009 international conference on Supporting group work
Automatic nonverbal analysis of social interaction in small groups: A review

Image and Vision Computing
Wearing a YouTube hat: directors, comedians, gurus, and user aggregated behavior

MM '09 Proceedings of the 17th ACM international conference on Multimedia
Modeling dominance in group conversations using nonverbal activity cues

IEEE Transactions on Audio, Speech, and Language Processing - Special issue on multimodal processing in speech-based interactions
Effective annotation and search for video blogs with integration of context and content analysis

IEEE Transactions on Multimedia - Special issue on integration of context and content
Crowdsourcing, attention and productivity

Journal of Information Science
Shot-boundary detection: unraveled and resolved?

IEEE Transactions on Circuits and Systems for Video Technology

Multi-modal social signal analysis for predicting agreement in conversation settings

Proceedings of the 15th ACM on International conference on multimodal interaction
Inferring mood in ubiquitous conversational video

Proceedings of the 12th International Conference on Mobile and Ubiquitous Multimedia

Quantified Score

Hi-index	0.00

Visualization

Abstract

We introduce the automatic analysis of conversational vlogs (VlogSense, for short) as a new research domain in social media. Conversational vlogs are inherently multimodal, depict natural behavior, and are suitable for large-scale analysis. Given their diversity in terms of content, VlogSense requires the integration of robust methods for multimodal analysis and for social media understanding. We present an original study on the automatic characterization of vloggers' audiovisual nonverbal behavior, grounded in work from social psychology and behavioral computing. Our study on 2,269 vlogs from YouTube shows that several nonverbal cues are significantly correlated with the social attention received by videos.