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Full-Text Articles in Social and Behavioral Sciences
Observatory Of Trends In Software Related Microblogs, Achananuparp Palakorn, Nelman Lubis Ibrahim, Yuan Tian, David Lo, Ee Peng Lim
Observatory Of Trends In Software Related Microblogs, Achananuparp Palakorn, Nelman Lubis Ibrahim, Yuan Tian, David Lo, Ee Peng Lim
David LO
Microblogging has recently become a popular means to disseminate information among millions of people. Interestingly, software developers also use microblog to communicate with one another. Different from traditional media, microblog users tend to focus on recency and informality of content. Many tweet contents are relatively more personal and Opinionated, compared to that of traditional news report. Thus, by analyzing microblogs, one could get the up-to-date information about what people are interested in or feel toward a particular topic. In this paper, we describe our microblog observatory that aggregates more than 70,000 Twitter feeds, captures software-related tweets, and computes trends from …
User Taglines: Alternative Presentations Of Expertise And Interest In Social Media, Hemant Purohit, Alex Dow, Omar Alonso, Lei Duan, Kevin Haas
User Taglines: Alternative Presentations Of Expertise And Interest In Social Media, Hemant Purohit, Alex Dow, Omar Alonso, Lei Duan, Kevin Haas
Kno.e.sis Publications
Web applications are increasingly showing recommended users from social media along with some descriptions, an attempt to show relevancy - why they are being shown. For example, Twitter search for a topical keyword shows expert twitterers on the side for 'whom to follow'. Google+ and Facebook also recommend users to follow or add to friend circle. Popular Internet newspaper- The Huffington Post shows Twitter influencers/ experts on the side of an article for authoritative relevant tweets. The state of the art shows user profile bios as summary for Twitter experts, but it has issues with length constraint imposed by user …
On Recommending Hashtags In Twitter Networks, Su Mon Kywe, Tuan-Anh Hoang, Ee Peng Lim, Feida Zhu
On Recommending Hashtags In Twitter Networks, Su Mon Kywe, Tuan-Anh Hoang, Ee Peng Lim, Feida Zhu
Research Collection School Of Computing and Information Systems
Twitter network is currently overwhelmed by massive amount of tweets generated by its users. To effectively organize and search tweets, users have to depend on appropriate hashtags inserted into tweets. We begin our research on hashtags by first analyzing a Twitter dataset generated by more than 150,000 Singapore users over a three-month period. Among several interesting findings about hashtag usage by this user community, we have found a consistent and significant use of new hashtags on a daily basis. This suggests that most hashtags have very short life span. We further propose a novel hashtag recommendation method based on collaborative …
Community-Based Classification Of Noun Phrases In Twitter, Freddy Chong Tat Chua, William W. Cohen, Justin Betterridge, Ee-Peng Lim
Community-Based Classification Of Noun Phrases In Twitter, Freddy Chong Tat Chua, William W. Cohen, Justin Betterridge, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Many event monitoring systems rely on counting known keywords in streaming text data to detect sudden spikes in frequency. But the dynamic and conversational nature of Twitter makes it hard to select known keywords for monitoring. Here we consider a method of automatically finding noun phrases (NPs) as keywords for event monitoring in Twitter. Finding NPs has two aspects, identifying the boundaries for the subsequence of words which represent the NP, and classifying the NP to a specific broad category such as politics, sports, etc. To classify an NP, we define the feature vector for the NP using not just …
A Survey Of Recommender Systems In Twitter, Su Mon Kywe, Ee Peng Lim, Feida Zhu
A Survey Of Recommender Systems In Twitter, Su Mon Kywe, Ee Peng Lim, Feida Zhu
Research Collection School Of Computing and Information Systems
Twitter is a social information network where short messages or tweets are shared among a large number of users through a very simple messaging mechanism. With a population of more than 100M users generating more than 300M tweets each day, Twitter users can be easily overwhelmed by the massive amount of information available and the huge number of people they can interact with. To overcome the above information overload problem, recommender systems can be introduced to help users make the appropriate selection. Researchers have began to study recommendation problems in Twitter but their works usually address individual recommendation tasks. There …
Observatory Of Trends In Software Related Microblogs, Achananuparp Palakorn, Nelman Lubis Ibrahim, Yuan Tian, David Lo, Ee Peng Lim
Observatory Of Trends In Software Related Microblogs, Achananuparp Palakorn, Nelman Lubis Ibrahim, Yuan Tian, David Lo, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Microblogging has recently become a popular means to disseminate information among millions of people. Interestingly, software developers also use microblog to communicate with one another. Different from traditional media, microblog users tend to focus on recency and informality of content. Many tweet contents are relatively more personal and Opinionated, compared to that of traditional news report. Thus, by analyzing microblogs, one could get the up-to-date information about what people are interested in or feel toward a particular topic. In this paper, we describe our microblog observatory that aggregates more than 70,000 Twitter feeds, captures software-related tweets, and computes trends from …
What Kind Of #Communication Is Twitter? A Psycholinguistic Perspective On Communication In Twitter For The Purpose Of Emergency Coordination, Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John Flach
What Kind Of #Communication Is Twitter? A Psycholinguistic Perspective On Communication In Twitter For The Purpose Of Emergency Coordination, Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John Flach
Kno.e.sis Publications
The present research aims to detect coordinated citizen response within social media traffic to assist emergency response. We use domain-independent linguistic properties as the first step in narrowing the candidate set of messages for domain-dependent and computationally intensive analysis.
Visualizing Media Bias Through Twitter, Jisun An, Meeyoung Cha, Gummadi, Krishna, Jon Crowcroft, Daniele Queria
Visualizing Media Bias Through Twitter, Jisun An, Meeyoung Cha, Gummadi, Krishna, Jon Crowcroft, Daniele Queria
Research Collection School Of Computing and Information Systems
Traditional media outlets are known to report political news in a biased way, potentially affecting the political beliefs of the audience and even altering their voting behaviors. Therefore, tracking bias in everyday news and building a platform where people can receive balanced news information is important. We propose a model that maps the news media sources along a dimensional dichotomous political spectrum using the co-subscriptions relationships inferred by Twitter links. By analyzing 7 million follow links, we show that the political dichotomy naturally arises on Twitter when we only consider direct media subscription. Furthermore, we demonstrate a real-time Twitter-based application …
Prediction Of Topic Volume On Twitter, Yiye Ruan, Hemant Purohit, David Fuhry, Srinivasan Parthasarathy, Amit P. Sheth
Prediction Of Topic Volume On Twitter, Yiye Ruan, Hemant Purohit, David Fuhry, Srinivasan Parthasarathy, Amit P. Sheth
Kno.e.sis Publications
We discuss an approach for predicting microscopic (individual) and macroscopic (collective) user behavioral patterns with respect to specific trending topics on Twitter. Going beyond previous efforts that have analyzed driving factors in whether and when a user will publish topic-relevant tweets, here we seek to predict the strength of content generation which allows more accurate understanding of Twitter users' behavior and more effective utilization of the online social network for diffusing information. Unlike traditional approaches, we consider multiple dimensions into one regression-based prediction framework covering network structure, user interaction, content characteristics and past activity. Experimental results on three large Twitter …
#Epicplay: Crowd-Sourcing Sports Video Highlights, Anthony Tang, Sebastian Boring
#Epicplay: Crowd-Sourcing Sports Video Highlights, Anthony Tang, Sebastian Boring
Research Collection School Of Computing and Information Systems
During a live sports event, many sports fans use social media as a part of their viewing experience, reporting on their thoughts on the event as it unfolds. In this work, we use this information stream to semantically annotate live broadcast sports games, using these annotations to select video highlights from the game. We demonstrate that this approach can be used to select highlights specific for fans of each team, and that these clips reflect the emotions of a fan during a game. Further, we describe how these clips differ from those seen on nightly sportscasts.
Social Networks And Web2.0 Among Youth: Lessons For Pacific Island Nations, Deogratias Harorimana Sr
Social Networks And Web2.0 Among Youth: Lessons For Pacific Island Nations, Deogratias Harorimana Sr
Dr Deogratias Harorimana
This study is on social networks and web2 among youths and the lessons for Pacific Island nation. This study defines commonly used social networking sites used by the Pacific youths, average time spent, reasons behind the use of social networking sites and how social networking sites can be used as a development tool for Pacific Island nation. It was found that the popularity of social networking amongst youths in Pacific Island Countries is fast growing, increasing more than three folds year on year in the last 3years. Social Networks are a vital part of life for PIC youths, where, now …
Extracting Diverse Sentiment Expressions With Target-Dependent Polarity From Twitter, Lu Chen, Wenbo Wang, Meenakshi Nagarajan, Shaojun Wang, Amit P. Sheth
Extracting Diverse Sentiment Expressions With Target-Dependent Polarity From Twitter, Lu Chen, Wenbo Wang, Meenakshi Nagarajan, Shaojun Wang, Amit P. Sheth
Kno.e.sis Publications
This study focuses on automatic extraction of sentiment expressions associated with given targets from Twitter. It addresses one of the key challenges in this work: Wide diversity and informal nature of sentiment expressions that cannot be trivially enumerated or captured using predefined lexical patterns.
Tweets And Votes: A Study Of The 2011 Singapore General Election, Marko M. Skoric, Nathaniel D. Poor, Palakorn Achananuparp, Ee Peng Lim, Jing Jiang
Tweets And Votes: A Study Of The 2011 Singapore General Election, Marko M. Skoric, Nathaniel D. Poor, Palakorn Achananuparp, Ee Peng Lim, Jing Jiang
Research Collection School Of Computing and Information Systems
This study focuses on the uses of Twitter during the elections, examining whether the messages posted online are reflective of the climate of public opinion. Using Twitter data obtained during the official campaign period of the 2011 Singapore General Election, we test the predictive power of tweets in forecasting the election results. In line with some previous studies, we find that during the elections the Twitter sphere represents a rich source of data for gauging public opinion and that the frequency of tweets mentioning names of political parties, political candidates and contested constituencies could be used to make predictions about …