{"title":"Finnish Liiga Corsi%-C Prediction Project","authors":"Brad Behan","doi":"10.2139/ssrn.3897337","DOIUrl":"https://doi.org/10.2139/ssrn.3897337","url":null,"abstract":"When searching the Finnish Liiga website for statistics, I discovered an interesting statistic called Corsi%-C. It is defined as “...when the score is within a goal in the first two periods and tied in the third period”. (liiga, 2021) Essentially, this is an enhanced version of Corsi for close game scenarios only. I was intrigued by this statistic and henceforth was motivated to begin this project to gain an understanding of the relationship between Corsi%-C and other metrics to see what attributes in players are more important in close game scenarios.","PeriodicalId":275824,"journal":{"name":"InfoSciRN: Other Data Science & Analytics (Topic)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129994112","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}
{"title":"The Role of Cyberinfrastructure-Enabled Collaboration Networks in Supporting Collaboration Capacity","authors":"Jian Qin, Jeff J Hemsley, Sarah E. Bratt","doi":"10.2139/ssrn.3887529","DOIUrl":"https://doi.org/10.2139/ssrn.3887529","url":null,"abstract":"This paper reports a study of the incremental impact of evolving cyberinfrastructure (CI) enabled collaboration networks on scientific capacity and knowledge diffusion. While ample research shows how collaboration contributes to greater productivity, higher-quality scientific outputs, and increased probability of breakthroughs, it is unclear how the early stages of collaboration on data creation supports knowledge generation and diffusion. Further, it is not known whether the ability to garner larger inputs increases collaboration capacity and subsequently accelerates the rate of knowledge diffusion. Given that the collaboration capacity of a science team is largely dependent upon the Scientific and Technical (S&T) Human Capital , the greater a researcher’s S&T human capital, the greater the opportunity to collaborate and access resources. We use “Collaboration Capacity” to refer to this measure of S&T human capital. In this study, we collected metadata for molecular sequences in GenBank from 1990-2013. The data contain details about sequences, submission date, submitter(s), and associated publications and authors. Based on the collaboration capacity framework (Figure 1), we focused on the relationship between collaboration network size and research productivity and the role of CI-enabled data repositories in accelerating collaboration capacity. Our preliminary results show that the size of CI-enabled collaboration networks at data creation stage was positively related to research productivity as measured by sequence data production, and the extent and rate of knowledge diffusion, represented by patent applications. Shrinking time gaps between data submissions and patent applications support the hypothesis that CIenabled data repositories are an accelerating factor in incremental collaboration capacity.","PeriodicalId":275824,"journal":{"name":"InfoSciRN: Other Data Science & Analytics (Topic)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124104982","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}
{"title":"Money and Privacy – Android Market Evidence","authors":"Michael E. Kummer, P. Schulte","doi":"10.2139/ssrn.2567164","DOIUrl":"https://doi.org/10.2139/ssrn.2567164","url":null,"abstract":"We study the role of privacy in the market for mobile applications. For such programs used with smartphones and tablet PCs a very important market has emerged. Yet, neither the role of privacy on that market is well understood, nor do we have empirical evidence regarding its role therein. We exploit data on 300,000 mobile applications and almost 600 \"applications-pairs\" to analyze both sides of this market: First, we analyze the price that application suppliers charge for more privacy. Second, we study how users' installations are related to the \"personal data greediness\" of mobile applications. We provide the first empirical evidence on the main assumptions of recent early models on suppliers' and consumers' strategies in this market. Our results show that (1) consumers take it into account when applications request rights to collect private information and (2) suppliers ask for more rights if they offer an app for free than if they offer it for a fee.","PeriodicalId":275824,"journal":{"name":"InfoSciRN: Other Data Science & Analytics (Topic)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115361268","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}