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Unlike some other reproductions of classic texts (1) We have not
used OCR(Optical Character Recognition), as this leads to bad
quality books with introduced typos. (2) In books where there are
images such as portraits, maps, sketches etc We have endeavoured to
keep the quality of these images, so they represent accurately the
original artefact. Although occasionally there may be certain
imperfections with these old texts, we feel they deserve to be made
available for future generations to enjoy.
This textbook provides a concise introduction to Management
Information Systems. It introduces core concepts in an accessible
style and adopts a contemporary approach that reflects the
opportunities and challenges faced as businesses and technologies
continue to evolve. Key features:
·       Coverage of key
issues including sustainability and green IT, ethics and privacy,
smart technologies, corporate social responsibility and big data
·       Definition boxes
to consolidate understanding of key terms
·       Illustrative
examples to engage and apply theory in the real-world
·       Pause for
thought boxes to check understanding and encourage reflection
·       End of chapter
case studies to illustrate key topics in practice, encourage
critical thinking, application of knowledge and enhance learning
·       Comprehensive
online support including PowerPoints, tutor’s guide and testbank
of questions This textbook is suitable for undergraduate and
postgraduate students studying introductory Management or Business
Information Systems courses with no prior knowledge. Dr Tomayess
Issa is a Senior Lecturer at Curtin University, Australia. Dr
Theodora Issa is a Senior Lecturer at Curtin University, Australia.
Dr Sarita Hardin-Ramanan is Head Faculty of IT at Curtin
University, Mauritius. Dr Bilal Abu Salih is a
Associate Professor at The University of Jordan, Jordan. Dr
Lydia Maketo is a Lecturer at Curtin University, Australia. Dr
Rohini Balapumi is a Lecturer at Curtin University, Australia. Dr
S. Zaung Nau is a Lecturer at Curtin University, Australia. Dr
Raadila Hajee Ahmud-Boodoo is a Teaching Instructor at Curtin
University, Australia.
This book focuses on data and how modern business firms use social
data, specifically Online Social Networks (OSNs) incorporated as
part of the infrastructure for a number of emerging applications
such as personalized recommendation systems, opinion analysis,
expertise retrieval, and computational advertising. This book
identifies how in such applications, social data offers a plethora
of benefits to enhance the decision making process. This book
highlights that business intelligence applications are more focused
on structured data; however, in order to understand and analyse the
social big data, there is a need to aggregate data from various
sources and to present it in a plausible format. Big Social Data
(BSD) exhibit all the typical properties of big data: wide physical
distribution, diversity of formats, non-standard data models,
independently-managed and heterogeneous semantics but even further
valuable with marketing opportunities. The book provides a review
of the current state-of-the-art approaches for big social data
analytics as well as to present dissimilar methods to infer value
from social data. The book further examines several areas of
research that benefits from the propagation of the social data. In
particular, the book presents various technical approaches that
produce data analytics capable of handling big data features and
effective in filtering out unsolicited data and inferring a value.
These approaches comprise advanced technical solutions able to
capture huge amounts of generated data, scrutinise the collected
data to eliminate unwanted data, measure the quality of the
inferred data, and transform the amended data for further data
analysis. Furthermore, the book presents solutions to derive
knowledge and sentiments from BSD and to provide social data
classification and prediction. The approaches in this book also
incorporate several technologies such as semantic discovery,
sentiment analysis, affective computing and machine learning. This
book has additional special feature enriched with numerous
illustrations such as tables, graphs and charts incorporating
advanced visualisation tools in accessible an attractive display.
This book focuses on data and how modern business firms use social
data, specifically Online Social Networks (OSNs) incorporated as
part of the infrastructure for a number of emerging applications
such as personalized recommendation systems, opinion analysis,
expertise retrieval, and computational advertising. This book
identifies how in such applications, social data offers a plethora
of benefits to enhance the decision making process. This book
highlights that business intelligence applications are more focused
on structured data; however, in order to understand and analyse the
social big data, there is a need to aggregate data from various
sources and to present it in a plausible format. Big Social Data
(BSD) exhibit all the typical properties of big data: wide physical
distribution, diversity of formats, non-standard data models,
independently-managed and heterogeneous semantics but even further
valuable with marketing opportunities. The book provides a review
of the current state-of-the-art approaches for big social data
analytics as well as to present dissimilar methods to infer value
from social data. The book further examines several areas of
research that benefits from the propagation of the social data. In
particular, the book presents various technical approaches that
produce data analytics capable of handling big data features and
effective in filtering out unsolicited data and inferring a value.
These approaches comprise advanced technical solutions able to
capture huge amounts of generated data, scrutinise the collected
data to eliminate unwanted data, measure the quality of the
inferred data, and transform the amended data for further data
analysis. Furthermore, the book presents solutions to derive
knowledge and sentiments from BSD and to provide social data
classification and prediction. The approaches in this book also
incorporate several technologies such as semantic discovery,
sentiment analysis, affective computing and machine learning. This
book has additional special feature enriched with numerous
illustrations such as tables, graphs and charts incorporating
advanced visualisation tools in accessible an attractive display.
This scarce antiquarian book is included in our special Legacy
Reprint Series. In the interest of creating a more extensive
selection of rare historical book reprints, we have chosen to
reproduce this title even though it may possibly have occasional
imperfections such as missing and blurred pages, missing text, poor
pictures, markings, dark backgrounds and other reproduction issues
beyond our control. Because this work is culturally important, we
have made it available as a part of our commitment to protecting,
preserving and promoting the world's literature.
This scarce antiquarian book is included in our special Legacy
Reprint Series. In the interest of creating a more extensive
selection of rare historical book reprints, we have chosen to
reproduce this title even though it may possibly have occasional
imperfections such as missing and blurred pages, missing text, poor
pictures, markings, dark backgrounds and other reproduction issues
beyond our control. Because this work is culturally important, we
have made it available as a part of our commitment to protecting,
preserving and promoting the world's literature.
This scarce antiquarian book is included in our special Legacy
Reprint Series. In the interest of creating a more extensive
selection of rare historical book reprints, we have chosen to
reproduce this title even though it may possibly have occasional
imperfections such as missing and blurred pages, missing text, poor
pictures, markings, dark backgrounds and other reproduction issues
beyond our control. Because this work is culturally important, we
have made it available as a part of our commitment to protecting,
preserving and promoting the world's literature.
This textbook provides a concise introduction to Management
Information Systems. It introduces core concepts in an accessible
style and adopts a contemporary approach that reflects the
opportunities and challenges faced as businesses and technologies
continue to evolve. Key features:
·       Coverage of key
issues including sustainability and green IT, ethics and privacy,
smart technologies, corporate social responsibility and big data
·       Definition boxes
to consolidate understanding of key terms
·       Illustrative
examples to engage and apply theory in the real-world
·       Pause for
thought boxes to check understanding and encourage reflection
·       End of chapter
case studies to illustrate key topics in practice, encourage
critical thinking, application of knowledge and enhance learning
·       Comprehensive
online support including PowerPoints, tutor’s guide and testbank
of questions This textbook is suitable for undergraduate and
postgraduate students studying introductory Management or Business
Information Systems courses with no prior knowledge. Dr Tomayess
Issa is a Senior Lecturer at Curtin University, Australia. Dr
Theodora Issa is a Senior Lecturer at Curtin University, Australia.
Dr Sarita Hardin-Ramanan is Head Faculty of IT at Curtin
University, Mauritius. Dr Bilal Abu Salih is a
Associate Professor at The University of Jordan, Jordan. Dr
Lydia Maketo is a Lecturer at Curtin University, Australia. Dr
Rohini Balapumi is a Lecturer at Curtin University, Australia. Dr
S. Zaung Nau is a Lecturer at Curtin University, Australia. Dr
Raadila Hajee Ahmud-Boodoo is a Teaching Instructor at Curtin
University, Australia.
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