University of Hertfordshire

By the same authors

Metadata Extraction and Classification of YouTube Videos Using Sentiment Analysis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Standard

Metadata Extraction and Classification of YouTube Videos Using Sentiment Analysis. / Ramalingam, Soodamani.

IEEE International Carnahan Conference on Security Technology: ICCST2016. US : IEEE 978-1-5090, 2016.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Ramalingam, S 2016, Metadata Extraction and Classification of YouTube Videos Using Sentiment Analysis. in IEEE International Carnahan Conference on Security Technology: ICCST2016. IEEE 978-1-5090, US, IEEE International Carnahan Conference on Security Technology, Orlando, Florida, United States, 24/10/16.

APA

Ramalingam, S. (2016). Metadata Extraction and Classification of YouTube Videos Using Sentiment Analysis. In IEEE International Carnahan Conference on Security Technology: ICCST2016 IEEE 978-1-5090.

Vancouver

Ramalingam S. Metadata Extraction and Classification of YouTube Videos Using Sentiment Analysis. In IEEE International Carnahan Conference on Security Technology: ICCST2016. US: IEEE 978-1-5090. 2016

Author

Ramalingam, Soodamani. / Metadata Extraction and Classification of YouTube Videos Using Sentiment Analysis. IEEE International Carnahan Conference on Security Technology: ICCST2016. US : IEEE 978-1-5090, 2016.

Bibtex

@inproceedings{ff2349166e55406fb4785ad4eb09e411,
title = "Metadata Extraction and Classification of YouTube Videos Using Sentiment Analysis",
abstract = "MPEG media have been widely adopted and is very successful in promoting interoperable services that deliver video to consumers on a range of devices. However, media consumption is going beyond the mere playback of a media asset and is geared towards a richer user experience that relies on rich metadata and content description. This paper proposes a technique for extracting and analysing metadata from a video, followed by decision making related to the video content. The system uses sentiment analysis for such a classification. It is envisaged that the system when fully developed, is to be applied to determine the existence of illicit multimedia content on the web.",
keywords = "MPEG, metadata extraction, video processing, sentiment analysis, polarity",
author = "Soodamani Ramalingam",
note = "Soodamani, R & Varsani, V (2016), Vehicle Detection for Traffic Flow Analysis, ICCST2016, Paper presented at the IEEE International Carnahan Conference on Security Technology, 24-27 October 2016, Orlando, Florida.; IEEE International Carnahan Conference on Security Technology ; Conference date: 24-10-2016 Through 27-10-2016",
year = "2016",
month = oct,
day = "24",
language = "English",
booktitle = "IEEE International Carnahan Conference on Security Technology",
publisher = "IEEE 978-1-5090",

}

RIS

TY - GEN

T1 - Metadata Extraction and Classification of YouTube Videos Using Sentiment Analysis

AU - Ramalingam, Soodamani

N1 - Soodamani, R & Varsani, V (2016), Vehicle Detection for Traffic Flow Analysis, ICCST2016, Paper presented at the IEEE International Carnahan Conference on Security Technology, 24-27 October 2016, Orlando, Florida.

PY - 2016/10/24

Y1 - 2016/10/24

N2 - MPEG media have been widely adopted and is very successful in promoting interoperable services that deliver video to consumers on a range of devices. However, media consumption is going beyond the mere playback of a media asset and is geared towards a richer user experience that relies on rich metadata and content description. This paper proposes a technique for extracting and analysing metadata from a video, followed by decision making related to the video content. The system uses sentiment analysis for such a classification. It is envisaged that the system when fully developed, is to be applied to determine the existence of illicit multimedia content on the web.

AB - MPEG media have been widely adopted and is very successful in promoting interoperable services that deliver video to consumers on a range of devices. However, media consumption is going beyond the mere playback of a media asset and is geared towards a richer user experience that relies on rich metadata and content description. This paper proposes a technique for extracting and analysing metadata from a video, followed by decision making related to the video content. The system uses sentiment analysis for such a classification. It is envisaged that the system when fully developed, is to be applied to determine the existence of illicit multimedia content on the web.

KW - MPEG

KW - metadata extraction

KW - video processing

KW - sentiment analysis

KW - polarity

M3 - Conference contribution

BT - IEEE International Carnahan Conference on Security Technology

PB - IEEE 978-1-5090

CY - US

T2 - IEEE International Carnahan Conference on Security Technology

Y2 - 24 October 2016 through 27 October 2016

ER -