2013 International Conference on Social Intelligence and Technology最新文献

Characterizing Communities of Practice in Emerging Science and Technology Fields 新兴科学和技术领域的实践社区特征

2013 International Conference on Social Intelligence and Technology Pub Date : 2013-05-08 DOI: 10.1109/SOCIETY.2013.9

O. Babko-Malaya, D. Hunter, Gregory Amis, P. Thomas, Adam Meyers, J. Pustejovsky, M. Verhagen

{"title":"Characterizing Communities of Practice in Emerging Science and Technology Fields","authors":"O. Babko-Malaya, D. Hunter, Gregory Amis, P. Thomas, Adam Meyers, J. Pustejovsky, M. Verhagen","doi":"10.1109/SOCIETY.2013.9","DOIUrl":"https://doi.org/10.1109/SOCIETY.2013.9","url":null,"abstract":"Emerging fields in science and technology are of great interest to innovation researchers, but such fields are often difficult to identify and characterize. This paper outlines a system for identifying a key element of emerging fields: their community of practice, consisting of active scientists and researchers. The system does not simply count these human actors and the interactions between them. Rather, guided by actant network theory, it also examines other non-human actors with which they interact, such as organizations, publications and terminologies. Using quantitative indicators inspired by actant network theory, and derived from features extracted from the full text and metadata of scientific publications and patents, the system attempts to identify communities of practice associated with emerging fields in science and technology. This paper outlines details of these features and indicators, describes how these indicators are combined using Bayesian models, and reports the results of applying these indicators to document sets associated with emerging scientific and technological fields. The results reported in this paper show that system outputs generally agree with subject matter expert judgments with respect to determining the existence of communities of practice, and appear to offer interesting insights into the development of emerging fields.","PeriodicalId":348108,"journal":{"name":"2013 International Conference on Social Intelligence and Technology","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128934720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Mining Social Media: Challenges and Opportunities 挖掘社交媒体:挑战与机遇

2013 International Conference on Social Intelligence and Technology Pub Date : 2013-05-08 DOI: 10.1109/SOCIETY.2013.12

Isaac Jones, Huan Liu

引用次数: 5

Question and Answering Made Interactive: An Exploration of Interactions in Social Q&A 问答互动:社交问答互动的探索

2013 International Conference on Social Intelligence and Technology Pub Date : 2013-05-08 DOI: 10.1109/SOCIETY.2013.16

Zhe Liu, B. Jansen

{"title":"Question and Answering Made Interactive: An Exploration of Interactions in Social Q&A","authors":"Zhe Liu, B. Jansen","doi":"10.1109/SOCIETY.2013.16","DOIUrl":"https://doi.org/10.1109/SOCIETY.2013.16","url":null,"abstract":"With the advancement of Web 2.0 techniques, social question and answering has become a new venue for individuals to seek for information online. Although it has been investigated by a number of works lately, so far still little has been known about how people interact with each other in order to satisfy their information needs in social Q&A. With the aim to understand the patterns of user interactions in the social Q&A context, as well as factors that may affect such kind of back-and-forth communications, in this work we collect over 1,000 question and answering dialogues from Sina Weibo. Statistical analyses including ANOVA, Pearson's correlation, linear regression and independent t-test are performed in order to answer our proposed research questions. Our results demonstrate the importance of studying the interactions in social Q&A given that about half of our collected question-answer pairs are of interactive nature. From the quantity perspective, we observe that questions within more complicated topics, such as \"Healthcare\" and \"Education\" generate more interactions. Significantly positive correlation is also noticed between social tie strength and the number of interactions. By manually annotating all interactive answers, we also indicate the importance of weak ties in providing high quality answers and interactions. Based on our results, we proposed potential implications for future design and implementations.","PeriodicalId":348108,"journal":{"name":"2013 International Conference on Social Intelligence and Technology","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122426564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Modeling Debate within a Scientific Community 科学界的建模辩论

2013 International Conference on Social Intelligence and Technology Pub Date : 2013-05-08 DOI: 10.1109/SOCIETY.2013.18

O. Babko-Malaya, Adam Meyers, J. Pustejovsky, M. Verhagen

引用次数: 8

A Method for Analyzing Influence of Emotions of Posts in SNS Conversations 社交网络对话中帖子情绪影响的分析方法

2013 International Conference on Social Intelligence and Technology Pub Date : 2013-05-08 DOI: 10.1109/SOCIETY.2013.8

Marina Fujita, J. Watanabe, Kentaro Kawamoto, Tomoaki Akitomi, Koji Ara

{"title":"A Method for Analyzing Influence of Emotions of Posts in SNS Conversations","authors":"Marina Fujita, J. Watanabe, Kentaro Kawamoto, Tomoaki Akitomi, Koji Ara","doi":"10.1109/SOCIETY.2013.8","DOIUrl":"https://doi.org/10.1109/SOCIETY.2013.8","url":null,"abstract":"We devised a method for analyzing communication, which focuses on influences between two sequential posts in a conversation on a social-network service (SNS). Posts expressed on an SNS are classified into three emotions: positive, negative, or neutral. Two influences were analyzed: the emotion of a person's preceding post on the emotion of a post from another person, and the emotion of a person's post on the emotion of a subsequent post from the same person. To analyze these influences, the basis of the frequency of emotional transitions of two sequential posts in actual conversational data is evaluated by probability and information entropy analysis. Three tendencies were found: first, a person who posted positively before is likely to post positively again, second, a neutral emotion of a person's post is more likely to be induced when both that person and another person expressed a neutral emotion in the past, third, negative posts do not have a strong influence on the emotion of subsequent posts of that person and other persons. These findings may be useful, for example, in promoting positive conversations.","PeriodicalId":348108,"journal":{"name":"2013 International Conference on Social Intelligence and Technology","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125728596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Leveraging User Interest to Improve Thread Recommendation in Online Forum 利用用户兴趣改进在线论坛的主题推荐

2013 International Conference on Social Intelligence and Technology Pub Date : 2013-05-08 DOI: 10.1109/SOCIETY.2013.13

Xuning Tang, Mi Zhang, Christopher C. Yang

{"title":"Leveraging User Interest to Improve Thread Recommendation in Online Forum","authors":"Xuning Tang, Mi Zhang, Christopher C. Yang","doi":"10.1109/SOCIETY.2013.13","DOIUrl":"https://doi.org/10.1109/SOCIETY.2013.13","url":null,"abstract":"Nowadays thread recommendation is considered to be beneficial to improve the end-user stickiness of an online forum. Given the fact of information overload and the diverse interests of forum users, a recommender system in online forum can satisfy not only forum users' information needs by directing them to what they might be interested in, but also their social needs by connecting them to their friends. Some traditional recommender systems rely on a bipartite graph model to capture users' interests. As an extension, some other content-based methods are proposed to further understand the potential connections between Web users and Web contents. However, due to the prevalence of short and sparse messages in online social media, it is hard for traditional content-based methods to capture Web users' interests. In this paper, we propose a novel graphical model to extract hidden topics from Web contents, cluster Web contents into clusters, and detect users' interests on each cluster. Then we introduce two reran king models which utilize the detected user interest to boost the performance of thread recommendation. Experiment results on a public dataset showed that our proposed methods substantially outperformed the naïve content-based approach. In addition, by testing our approaches with different parameter settings, we observed, to some extent, how forum users' information needs and their social needs interplay to decide which threads they will look for.","PeriodicalId":348108,"journal":{"name":"2013 International Conference on Social Intelligence and Technology","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134285115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Disclosing Climate Change Patterns Using an Adaptive Markov Chain Pattern Detection Method 利用自适应马尔可夫链模式检测方法揭示气候变化模式

2013 International Conference on Social Intelligence and Technology Pub Date : 2013-05-08 DOI: 10.1109/SOCIETY.2013.15

Zhaoxia Wang, G. Lee, H. Chan, R. Li, Xiuju FU, R. Goh, Pauline Aw, M. Hibberd, H. Chin

{"title":"Disclosing Climate Change Patterns Using an Adaptive Markov Chain Pattern Detection Method","authors":"Zhaoxia Wang, G. Lee, H. Chan, R. Li, Xiuju FU, R. Goh, Pauline Aw, M. Hibberd, H. Chin","doi":"10.1109/SOCIETY.2013.15","DOIUrl":"https://doi.org/10.1109/SOCIETY.2013.15","url":null,"abstract":"This paper proposes an adaptive Markov chain pattern detection (AMCPD) method for disclosing the climate change patterns of Singapore through meteorological data mining. Meteorological variables, including daily mean temperature, mean dew point temperature, mean visibility, mean wind speed, maximum sustained wind speed, maximum temperature and minimum temperature are simultaneously considered for identifying climate change patterns in this study. The results depict various weather patterns from 1962 to 2011 in Singapore, based on the records of the Changi Meteorological Station. Different scenarios with varied cluster thresholds are employed for testing the sensitivity of the proposed method. The robustness of the proposed method is demonstrated by the results. It is observed from the results that the early weather patterns that were present from the 1960s disappear consistently across models. Changes in temporal weather patterns suggest long-term changes to the climate of Singapore which may be attributed in part to urban development, and global climate change on a larger scale. Our climate change pattern detection algorithm is proven to be of potential use for climatic and meteorological research as well as research focusing on temporal trends in weather and the consequent changes.","PeriodicalId":348108,"journal":{"name":"2013 International Conference on Social Intelligence and Technology","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130199765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

From Data to Human Behaviour 从数据到人类行为

2013 International Conference on Social Intelligence and Technology Pub Date : 2013-05-08 DOI: 10.1109/SOCIETY.2013.14

Przemyslaw Kazienko, Tomasz Kajdanowicz, Radosław Michalski, Piotr Bródka

引用次数: 0

The Maximum Community Partition Problem in Networks 网络中的最大团体划分问题

2013 International Conference on Social Intelligence and Technology Pub Date : 2013-05-08 DOI: 10.1142/S1793830913500316

Zaixin Lu, Weili Wu, Weidong Chen, Jiaofei Zhong, Yuanjun Bi, Zheng Gao

引用次数: 10

RT^2M: Real-Time Twitter Trend Mining System RT^2M:实时Twitter趋势挖掘系统

2013 International Conference on Social Intelligence and Technology Pub Date : 2013-05-08 DOI: 10.1109/SOCIETY.2013.19

Min Song, Meen Chul Kim

{"title":"RT^2M: Real-Time Twitter Trend Mining System","authors":"Min Song, Meen Chul Kim","doi":"10.1109/SOCIETY.2013.19","DOIUrl":"https://doi.org/10.1109/SOCIETY.2013.19","url":null,"abstract":"The advent of social media is changing the existing information behavior by letting users access to real-time online information channels without the constraints of time and space. It also generates a huge amount of data worth discovering novel knowledge. Social media, therefore, has created an enormous challenge for scientists trying to keep pace with developments in their field. Most of the previous studies have adopted broad-brush approaches which tend to result in providing limited analysis. To handle these problems properly, we introduce our real-time Twitter trend mining system, RT2M, which operates in real-time to process big stream datasets available on Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, Topic Modeling to keep track of changes of topical trend, and analysis on mention-based user networks. We also demonstrate an empirical study on 2012 Korean presidential election. The case study reveals Twitter could be a useful source to detect and predict the advent and changes of social issues, and analysis of mention-based user networks could show different aspects of user behaviors.","PeriodicalId":348108,"journal":{"name":"2013 International Conference on Social Intelligence and Technology","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128735478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 18