عنوان

Investigations in computational sarcasm /

(Number (ISBN

9789811083969

(Number (ISBN

9789811083976

(Number (ISBN

9789811341397

(Number (ISBN

9811083967

(Number (ISBN

9811083975

(Number (ISBN

9811341397

Erroneous ISBN

9789811083952

Erroneous ISBN

9811083959

Title Proper

Investigations in computational sarcasm /

General Material Designation

[Book]

First Statement of Responsibility

Aditya Joshi, Pushpak Bhattacharyya, Mark J. Carman.

Place of Publication, Distribution, etc.

Singapore :

Name of Publisher, Distributor, etc.

Springer,

Date of Publication, Distribution, etc.

2018.

Specific Material Designation and Extent of Item

1 online resource (XII, 143 pages) :

Other Physical Details

illustrations

Series Title

Cognitive Systems Monographs,

Volume Designation

37

ISSN of Series

1867-4925 ;

Text of Note

Includes bibliographical references.

Text of Note

1. Introduction -- 2. Literature Survey -- 3. Understanding the Phenomenon of Sarcasm -- 4. Sarcasm Detection using Incongruity within Target Text -- 5. Sarcasm Detection using Contextual Incongruity -- 6. Sarcasm Generation -- 7. Conclusion & Future Work.

0

Text of Note

This book describes the authors' investigations of computational sarcasm based on the notion of incongruity. In addition, it provides a holistic view of past work in computational sarcasm and the challenges and opportunities that lie ahead. Sarcastic text is a peculiar form of sentiment expression and computational sarcasm refers to computational techniques that process sarcastic text. To first understand the phenomenon of sarcasm, three studies are conducted: (a) how is sarcasm annotation impacted when done by non-native annotators? (b) How is sarcasm annotation impacted when the task is to distinguish between sarcasm and irony? And (c) can targets of sarcasm be identified by humans and computers. Following these studies, the book proposes approaches for two research problems: sarcasm detection and sarcasm generation. To detect sarcasm, incongruity is captured in two ways: 'intra-textual incongruity' where the authors look at incongruity within the text to be classified (i.e., target text) and 'context incongruity' where the authors incorporate information outside the target text. These approaches use machine-learning techniques such as classifiers, topic models, sequence labelling, and word embeddings. These approaches operate at multiple levels: (a) sentiment incongruity (based on sentiment mixtures), (b) semantic incongruity (based on word embedding distance), (c) language model incongruity (based on unexpected language model), (d) author's historical context (based on past text by the author), and (e) conversational context (based on cues from the conversation). In the second part of the book, the authors present the first known technique for sarcasm generation, which uses a template-based approach to generate a sarcastic response to user input. This book will prove to be a valuable resource for researchers working on sentiment analysis, especially as applied to automation in social media.

Source for Acquisition/Subscription Address

Springer Nature

Stock Number

com.springer.onix.9789811083969

International Standard Book Number

9789811083952

Computational intelligence.

Irony.

Text processing (Computer science)

Computational intelligence.

Computational linguistics.

COMPUTERS-- General.

Engineering.

COM-- 000000

COM004000

UYQ

UYQ

Number

Edition

Class number

Joshi, Aditya

Bhattacharyya, Pushpak

Carman, Mark J.

Date of Transaction

20200823222603.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

Y