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Computational Analysis of Communication

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ISBN: 9781119680239 Category:

<p><b>Provides clear guidance on leveraging&nbsp;</b><b>computational techniques to&nbsp;answer&nbsp;social science questions</b>&nbsp;</p> <p>In disciplines such as political science, sociology,&nbsp;psychology,&nbsp;and media studies,&nbsp;the use of computational analysis is rapidly increasing. Statistical modeling, machine learning, and other computational techniques are revolutionizing the way electoral results are predicted, social sentiment is measured, consumer interest is evaluated, and much more.&nbsp;<i>Computational Analysis of Communication&nbsp;</i>teaches&nbsp;social science students and practitioners&nbsp;how<i>&nbsp;</i>computational methods<i>&nbsp;</i>can be used in a&nbsp;broad&nbsp;range of applications, providing&nbsp;discipline-relevant examples, clear&nbsp;explanations, and practical guidance.&nbsp;&nbsp;&nbsp;</p> <p>Assuming little or no background in&nbsp;data&nbsp;science&nbsp;or&nbsp;computer linguistics, this accessible&nbsp;textbook&nbsp;teaches&nbsp;readers&nbsp;how to use state-of-the art computational methods&nbsp;to&nbsp;perform&nbsp;data-driven analyses of social science issues.&nbsp;A&nbsp;cross-disciplinary team&nbsp;of authors&mdash;with expertise in&nbsp;both the&nbsp;social sciences and computer science&mdash;explains&nbsp;how to&nbsp;gather&nbsp;and clean data, manage&nbsp;textual, audio-visual, and network data, conduct statistical and quantitative analysis, and interpret,&nbsp;summarize,&nbsp;and&nbsp;visualize&nbsp;the results.&nbsp;Offered in a&nbsp;unique&nbsp;hybrid&nbsp;format that integrates&nbsp;print, ebook,&nbsp;and&nbsp;open-access online&nbsp;viewing, this innovative resource:&nbsp;</p> <ul style=”margin-bottom: 0in; font-size: medium; margin-top: 0in;” type=”disc”> <li style=”margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif; vertical-align: baseline;”>Covers the essential skills for social sciences courses on big data, data visualization, text analysis, predictive analytics, and others&nbsp;</li> <li style=”margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif; vertical-align: baseline; user-select: text; -webkit-user-drag: none; -webkit-tap-highlight-color: transparent; cursor: text; overflow: visible;”>Integrates theory, methods, and tools to provide unified approach to the subject&nbsp;</li> <li style=”margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif; vertical-align: baseline; user-select: text; -webkit-user-drag: none; -webkit-tap-highlight-color: transparent; cursor: text; overflow: visible;”>Includes sample code in Python and links to actual research questions and cases from social science and communication studies&nbsp;</li> <li style=”margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif; vertical-align: baseline; user-select: text; -webkit-user-drag: none; -webkit-tap-highlight-color: transparent; cursor: text; overflow: visible;”>Discusses&nbsp;ethical and normative&nbsp;issues&nbsp;relevant to&nbsp;privacy, data ownership, and reproducible social science&nbsp;</li> <li style=”margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif; vertical-align: baseline; user-select: text; -webkit-user-drag: none; -webkit-tap-highlight-color: transparent; cursor: text; overflow: visible;”>Developed in partnership with the International Communication Association and by the editors of&nbsp;<i>Computational Communication Research</i>&nbsp;</li> </ul> <p><i>Computational Analysis of Communication</i><i>&nbsp;</i>is an invaluable textbook and reference for&nbsp;students taking&nbsp;computational methods courses in social sciences,&nbsp;and for&nbsp;professional social scientists looking to&nbsp;incorporate&nbsp;computational methods&nbsp;into their work.&nbsp;</p>