{"title":"Data Analytics Process: An Application Case on Predicting Student Attrition","authors":"D. Delen","doi":"10.1201/9781315209555-2","DOIUrl":"https://doi.org/10.1201/9781315209555-2","url":null,"abstract":"","PeriodicalId":368732,"journal":{"name":"Analytics and Knowledge Management","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131865409","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":"Transactional Value Analytics in Organizational Development","authors":"C. Stary","doi":"10.1201/9781315209555-8","DOIUrl":"https://doi.org/10.1201/9781315209555-8","url":null,"abstract":"","PeriodicalId":368732,"journal":{"name":"Analytics and Knowledge Management","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126624519","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":"Data Analytics for Deriving Knowledge from User Feedback","authors":"K. Chahal, S. Kapur","doi":"10.1201/9781315209555-4","DOIUrl":"https://doi.org/10.1201/9781315209555-4","url":null,"abstract":"","PeriodicalId":368732,"journal":{"name":"Analytics and Knowledge Management","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134506941","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}
Pub Date : 2018-08-06DOI: 10.1201/9781315209555-10
Mahmoud Elbattah, O. Molloy
{"title":"Analytics Using Machine Learning-Guided Simulations with Application to Healthcare Scenarios","authors":"Mahmoud Elbattah, O. Molloy","doi":"10.1201/9781315209555-10","DOIUrl":"https://doi.org/10.1201/9781315209555-10","url":null,"abstract":"","PeriodicalId":368732,"journal":{"name":"Analytics and Knowledge Management","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125705578","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}
Jiangping Chen, B. R. Ayala, Duha Alsmadi, Guonan Wang
Data have been frequently discussed along with two other concepts: information and knowledge. However, the concept of data seems less ambiguous than that of information or knowledge. Data are considered to be symbols, or raw facts which have not yet been processed (Ackoff, 1989; Coronel, Morris, & Rob, 2012, p.5). In contrast, information has a number of different definitions, such as information as a thing, something informative, a process, or equivalent to knowledge (Buckland, 1991; Losee, 1997; Saracevic, 1999; Madden, 2000). Knowledge also does not have an agreed-upon definition. Davenport and Prusak (1998) viewed knowledge as “a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information.” (Davenport & Prusak, 1998, p.5).
{"title":"Fundamentals of Data Science for Future Data Scientists","authors":"Jiangping Chen, B. R. Ayala, Duha Alsmadi, Guonan Wang","doi":"10.1201/9781315209555-6","DOIUrl":"https://doi.org/10.1201/9781315209555-6","url":null,"abstract":"Data have been frequently discussed along with two other concepts: information and knowledge. However, the concept of data seems less ambiguous than that of information or knowledge. Data are considered to be symbols, or raw facts which have not yet been processed (Ackoff, 1989; Coronel, Morris, & Rob, 2012, p.5). In contrast, information has a number of different definitions, such as information as a thing, something informative, a process, or equivalent to knowledge (Buckland, 1991; Losee, 1997; Saracevic, 1999; Madden, 2000). Knowledge also does not have an agreed-upon definition. Davenport and Prusak (1998) viewed knowledge as “a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information.” (Davenport & Prusak, 1998, p.5).","PeriodicalId":368732,"journal":{"name":"Analytics and Knowledge Management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130716916","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}
Pub Date : 2018-08-06DOI: 10.1201/9781315209555-11
G. Erickson, Helen N. Rothberg
{"title":"Intangible Dynamics: Knowledge Assets in the Context of Big Data and Business Intelligence","authors":"G. Erickson, Helen N. Rothberg","doi":"10.1201/9781315209555-11","DOIUrl":"https://doi.org/10.1201/9781315209555-11","url":null,"abstract":"","PeriodicalId":368732,"journal":{"name":"Analytics and Knowledge Management","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121940133","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}
Course Description Social media plays a key role in campaigns and the daily work of marketing, public relations and advertising researchers and professionals. This class will integrate the growing research in the area with the social media practices in these industries. This class will focus on the three underpinnings of a successful social media activity: Analytics, Listening and Engagement. Analytics: Understanding social media metrics, measurements and evaluations. In studying social media, one objective of this class is to help students make a conceptual shift from thinking about groups of primarily passive audiences to individuals who consume, create and exchange content. This calls for a focus on patterns of interactions among users on social media to identifying communities and influential users within topical contexts. Some of the applications that will be used are Facebook Analytics, Twitter Analytics, Excel and NodeXL (for network analysis). Strategic listening: We will use a range of social media monitoring services and data collection tools to follow targeted social media conversations. This availability of large data requires a strategic and prioritized listening. Strategic listening means monitoring posted content in the context of users’ social interactions, focusing on key users and communities. We will use Brand24 as a social media monitoring/listening tool. Engagement: Students will work throughout the semester to evaluate social media presence and activity of an organization of their choice. Students will study the social media environments of oncampus clients, evaluate the success of their activity and write a report.
{"title":"Social Media Analytics","authors":"Miyoung Chong, Hsia-Ching Chang","doi":"10.1201/9781315209555-7","DOIUrl":"https://doi.org/10.1201/9781315209555-7","url":null,"abstract":"Course Description Social media plays a key role in campaigns and the daily work of marketing, public relations and advertising researchers and professionals. This class will integrate the growing research in the area with the social media practices in these industries. This class will focus on the three underpinnings of a successful social media activity: Analytics, Listening and Engagement. Analytics: Understanding social media metrics, measurements and evaluations. In studying social media, one objective of this class is to help students make a conceptual shift from thinking about groups of primarily passive audiences to individuals who consume, create and exchange content. This calls for a focus on patterns of interactions among users on social media to identifying communities and influential users within topical contexts. Some of the applications that will be used are Facebook Analytics, Twitter Analytics, Excel and NodeXL (for network analysis). Strategic listening: We will use a range of social media monitoring services and data collection tools to follow targeted social media conversations. This availability of large data requires a strategic and prioritized listening. Strategic listening means monitoring posted content in the context of users’ social interactions, focusing on key users and communities. We will use Brand24 as a social media monitoring/listening tool. Engagement: Students will work throughout the semester to evaluate social media presence and activity of an organization of their choice. Students will study the social media environments of oncampus clients, evaluate the success of their activity and write a report.","PeriodicalId":368732,"journal":{"name":"Analytics and Knowledge Management","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115376145","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}
Nicholas E. Evangelopoulos, S. Shakeri, Andrea R. Bennett
{"title":"Transforming Knowledge Sharing in Twitter-Based Communities Using Social Media Analytics","authors":"Nicholas E. Evangelopoulos, S. Shakeri, Andrea R. Bennett","doi":"10.1201/9781315209555-3","DOIUrl":"https://doi.org/10.1201/9781315209555-3","url":null,"abstract":"","PeriodicalId":368732,"journal":{"name":"Analytics and Knowledge Management","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115174904","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}
Pub Date : 2018-08-06DOI: 10.1201/9781315209555-12
Denise A. D. Bedford
{"title":"Analyzing Data and Words—Guiding Principles and Lessons Learned","authors":"Denise A. D. Bedford","doi":"10.1201/9781315209555-12","DOIUrl":"https://doi.org/10.1201/9781315209555-12","url":null,"abstract":"","PeriodicalId":368732,"journal":{"name":"Analytics and Knowledge Management","volume":"166 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122425442","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":"Knowledge Management for Action-Oriented Analytics","authors":"J. Edwards, E. Rodriguez","doi":"10.1201/9781315209555-1","DOIUrl":"https://doi.org/10.1201/9781315209555-1","url":null,"abstract":"","PeriodicalId":368732,"journal":{"name":"Analytics and Knowledge Management","volume":"176 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116006624","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}
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