When a friend online is more than a friend in life: Intimate relationship prediction in microblogs

Microblogging services such as Twitter and Sina Weibo have been an important, if not indespensible, platform for people around the world to connect to one another. The rich content and user interactions on these platforms reveal insightful information about each user that are valuable for various re...

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Main Authors: LAN, Yunshi, ZHANG, Mengqi, ZHU, Feida, JIANG, Jing, LIM, Ee-Peng
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Language:English
Published: Institutional Knowledge at Singapore Management University 2016
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Online Access:https://ink.library.smu.edu.sg/sis_research/3377
https://ink.library.smu.edu.sg/context/sis_research/article/4378/viewcontent/When_a_friend_online.pdf
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spelling sg-smu-ink.sis_research-43782018-06-13T04:41:19Z When a friend online is more than a friend in life: Intimate relationship prediction in microblogs LAN, Yunshi ZHANG, Mengqi ZHU, Feida JIANG, Jing LIM, Ee-Peng Microblogging services such as Twitter and Sina Weibo have been an important, if not indespensible, platform for people around the world to connect to one another. The rich content and user interactions on these platforms reveal insightful information about each user that are valuable for various real-life applications. In particular, user offline relationships, especially those intimate ones such as family members and couples, offer distinctive value for many business and social settings. In this study, we focus on using Sina Weibo to discover intimate offline relationships among users. The problem is uniquely interesting and challenging due to the difficulty in mining such sensitive and implicit knowledge across the online-offline boundary. We introduce deep learning approaches to this relationship identity problem and adopt an integrated model to capture features from both user profile and mention message. Our experiments on real data demonstrate the effectiveness of our approach. In addition, we present interesting findings from behavior between intimate users in terms of user features and interaction patterns. 2016-09-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3377 info:doi/10.1007/978-3-319-45814-4_16 https://ink.library.smu.edu.sg/context/sis_research/article/4378/viewcontent/When_a_friend_online.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Intimate relationship Relationship identification Deep learning Microblogging platform Computer Sciences Social Media
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Intimate relationship
Relationship identification
Deep learning
Microblogging platform
Computer Sciences
Social Media
spellingShingle Intimate relationship
Relationship identification
Deep learning
Microblogging platform
Computer Sciences
Social Media
LAN, Yunshi
ZHANG, Mengqi
ZHU, Feida
JIANG, Jing
LIM, Ee-Peng
When a friend online is more than a friend in life: Intimate relationship prediction in microblogs
description Microblogging services such as Twitter and Sina Weibo have been an important, if not indespensible, platform for people around the world to connect to one another. The rich content and user interactions on these platforms reveal insightful information about each user that are valuable for various real-life applications. In particular, user offline relationships, especially those intimate ones such as family members and couples, offer distinctive value for many business and social settings. In this study, we focus on using Sina Weibo to discover intimate offline relationships among users. The problem is uniquely interesting and challenging due to the difficulty in mining such sensitive and implicit knowledge across the online-offline boundary. We introduce deep learning approaches to this relationship identity problem and adopt an integrated model to capture features from both user profile and mention message. Our experiments on real data demonstrate the effectiveness of our approach. In addition, we present interesting findings from behavior between intimate users in terms of user features and interaction patterns.
format text
author LAN, Yunshi
ZHANG, Mengqi
ZHU, Feida
JIANG, Jing
LIM, Ee-Peng
author_facet LAN, Yunshi
ZHANG, Mengqi
ZHU, Feida
JIANG, Jing
LIM, Ee-Peng
author_sort LAN, Yunshi
title When a friend online is more than a friend in life: Intimate relationship prediction in microblogs
title_short When a friend online is more than a friend in life: Intimate relationship prediction in microblogs
title_full When a friend online is more than a friend in life: Intimate relationship prediction in microblogs
title_fullStr When a friend online is more than a friend in life: Intimate relationship prediction in microblogs
title_full_unstemmed When a friend online is more than a friend in life: Intimate relationship prediction in microblogs
title_sort when a friend online is more than a friend in life: intimate relationship prediction in microblogs
publisher Institutional Knowledge at Singapore Management University
publishDate 2016
url https://ink.library.smu.edu.sg/sis_research/3377
https://ink.library.smu.edu.sg/context/sis_research/article/4378/viewcontent/When_a_friend_online.pdf
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