Metadata Extraction and Classification of YouTube Videos Using Sentiment Analysis

Soodamani Ramalingam

Metadata Extraction and Classification of YouTube Videos Using Sentiment Analysis

Soodamani Ramalingam

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

26 Citations (Scopus)

280 Downloads (Pure)

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.

Original language	English
Title of host publication	IEEE International Carnahan Conference on Security Technology
Subtitle of host publication	ICCST2016
Place of Publication	US
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Number of pages	7
Publication status	Published - 24 Oct 2016
Event	IEEE International Carnahan Conference on Security Technology - US, Orlando, Florida, United States Duration: 24 Oct 2016 → 27 Oct 2016

Conference

Conference	IEEE International Carnahan Conference on Security Technology
Country/Territory	United States
City	Orlando, Florida
Period	24/10/16 → 27/10/16

Keywords

MPEG
metadata extraction
video processing
sentiment analysis
polarity

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Rangaswamy Metadata-Extraction-And-Classification-Of-Youtube-Videos-Usin...Accepted author manuscript, 442 KB

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@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 = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

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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 - Institute of Electrical and Electronics Engineers (IEEE)

CY - US

T2 - IEEE International Carnahan Conference on Security Technology

Y2 - 24 October 2016 through 27 October 2016

ER -

Metadata Extraction and Classification of YouTube Videos Using Sentiment Analysis

Abstract

Conference

Keywords

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