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Jean Burgess,
Kim Osman,
Axel Bruns,
Tim Highfield,
Ehsan Dehghan,
Edward Hurcombe,
and
Silvia Montana
Most FutureLearn courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts. Find out more This course is for anyone who wants to gain insight into social media analysis, develop a critical understanding of how digital media are used and gain skills using three digital tools. This course will allow learners without coding skills to access, analyse and visualise their own social media data.
Topics Covered
Read more
Most FutureLearn courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts. Find out more This course is for anyone who wants to gain insight into social media analysis, develop a critical understanding of how digital media are used and gain skills using three digital tools. This course will allow learners without coding skills to access, analyse and visualise their own social media data.
Topics Covered
Read more
Most FutureLearn courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts. Find out more This course is for anyone who wants to gain insight into social media analysis, develop a critical understanding of how digital media are used and gain skills using three digital tools. This course will allow learners without coding skills to access, analyse and visualise their own social media data.
Topics Covered
- The role and structures of social media conversations
- Methods for and implications of gathering data
- Key metrics used for analysing Twitter
- Methods for identifying trends in social data
- The theory of social networks
- Methods for creating and interpreting data visualisations
Register for this course and see more details by visiting:
OpenCourser.com/course/tbh3pd/social
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Reviews summary
Social media analytics: introduction for non-coders
According to learners, Social Media Analytics: Using Data to Understand Public Conversations is a largely positive experience, particularly for those new to the field. Students say it provides a solid foundation in understanding social media conversations and analytics concepts. Many find the clear explanations and useful tools and demonstrations helpful, especially for non-coders. However, some reviewers feel the course lacks depth for intermediate learners and note that the tools and data can feel outdated, a potential concern for those seeking the latest techniques. Overall, it's seen as a strong introductory course but may require supplemental learning for advanced application.
Practical tool demos found helpful.
"Found the tool demonstrations very useful and practical."
"The practical part with tools was helpful..."
"The data visualization module was particularly good."
"I appreciated the practical examples and tool walkthroughs provided."
Concepts and theory are explained simply.
"Excellent course covering key concepts... explanations were clear."
"Explained complex ideas clearly."
"The network analysis concepts were well explained."
"I found the concepts to be presented in a very understandable way."
Provides a strong intro for newcomers to analytics.
"Really enjoyed this course. It gave me a solid foundation for understanding public conversations online."
"Fantastic introductory course! It demystifies social media data analysis for non-programmers."
"Useful course for beginners. Explained complex ideas clearly. ... a good starting point."
"I feel I have gained a solid foundation in social media analytics after taking this course."
Challenges with assignments or support noted.
"I struggled with some of the assignments and wished there was more support. Forum wasn't very active."
May be too basic for experienced learners.
"Decent introduction. Covers the basics but doesn't go into much depth."
"The course is okay, but it's quite basic. If you already know a bit... this might be too elementary."
"Provides a good starting point but you'll need more advanced courses for deeper skills."
Tools and data used may not be current.
"Disappointed... The tools used felt outdated, and the data provided was not current."
"Outdated information and tools. The course needs a major update."
"Some data sets seemed a little old."
"I expected more practical, hands-on exercises using current platforms."
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Social Media Analytics: Using Data to Understand Public Conversations.
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Learners who complete Social Media Analytics: Using Data to Understand Public Conversations will develop knowledge and skills
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For more career information including salaries, visit:
OpenCourser.com/course/tbh3pd/social
Reading list
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Provides a comprehensive overview of social media data analysis, including how to collect, clean, and analyze social media data to extract meaningful insights. It is particularly strong in its coverage of using social media data analysis to understand user behavior and trends.
Provides a comprehensive overview of social media marketing, including how to develop and implement effective social media campaigns. It is particularly strong in its coverage of using social media marketing to generate leads and drive sales.
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Provides a practical guide to social media marketing, including how to develop and implement effective social media campaigns. It is particularly strong in its coverage of using social media marketing to generate leads and drive sales.
Provides a practical guide to social media measurement, including how to set social media goals, track key metrics, and analyze your results. It is particularly strong in its coverage of using social media measurement to improve your social media marketing efforts.
Provides a practical guide to social media marketing, including how to develop and implement effective social media campaigns. It is particularly strong in its coverage of using social media marketing to generate leads and drive sales.
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Provides a practical guide to social media marketing, including how to develop and implement effective social media campaigns. It is particularly strong in its coverage of using social media marketing to generate leads and drive sales.
Provides a practical guide to social media marketing, including how to develop and implement effective social media campaigns. It is particularly strong in its coverage of using social media marketing to generate leads and drive sales.
Provides a practical, code-centric approach to social media analysis, offering hands-on examples using Python. It is highly relevant for those looking to understand how to extract and work with data from various social media platforms. While some platform-specific APIs may change over time, the underlying principles and techniques for data mining remain valuable, making it a useful reference for practitioners and students alike.
Provides a strong foundation in the fundamental principles of data science and data-analytic thinking, which are essential for effective social media analysis. It helps in understanding how to extract useful knowledge and business value from data. While not exclusively focused on social media, its concepts are directly applicable and provide necessary background knowledge for anyone serious about analyzing social media data for business insights.
Offers an interdisciplinary approach to understanding networks and collective behavior, drawing on economics, sociology, and computer science. It provides foundational knowledge about how individuals interact within connected systems, which is highly relevant to understanding the dynamics of social media. It's often used as a textbook and is valuable for gaining a broad understanding of the underlying principles of social networks.
This handbook offers a comprehensive overview of the various methods used in social media research. It is an excellent reference tool for researchers and students looking to understand the different approaches to collecting, analyzing, and interpreting social media data. It covers a wide range of topics, providing both breadth and depth to the understanding of social media analysis methodologies.
This practical guide focuses on using Python for social media analytics. It covers acquiring, cleaning, and analyzing social media data using Python libraries. It's particularly useful for those who want to apply programming skills to social media analysis and gain hands-on experience with relevant tools and techniques.
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Explores the impact of personalization algorithms on the information we consume online, including on social media. It provides crucial context on how social media platforms shape user experiences and can lead to filter bubbles and echo chambers. While not a technical analysis book, it must-read for understanding the broader societal implications of social media and the data it generates.
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Offers an inside look at media manipulation and how information spreads online, particularly through blogs and social media. It provides valuable insights into the less visible aspects of online information dissemination and the potential for manipulation, which is relevant for anyone analyzing social media trends and narratives. It's more of a supplementary reading to provide a critical perspective.
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Examines how the internet and social tools facilitate group action and organization without traditional structures. It provides a foundational understanding of the social and organizational impact of connected technologies, which is highly relevant to the study of social media. It's considered a classic in understanding the early impact of social technologies.
This textbook provides a unified introduction to computational social science, covering methodologies relevant to social media analysis such as automated social information extraction and social network analysis. It's suitable for undergraduates and provides a solid theoretical and methodological background for analyzing social phenomena using computational methods.
Focuses on algorithms for mining massive datasets, with many examples drawn from the web and online media. While not solely focused on social media, the techniques covered are directly applicable to analyzing large-scale social media data. It's a valuable resource for understanding the computational challenges and approaches to big data analysis in the context of social platforms and is often used in computer science programs.
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Social media data is often in text format, making this book highly relevant for analyzing the content of social media interactions. It introduces a framework for using text as data in social science research, incorporating machine learning techniques. is valuable for those looking to perform in-depth analysis of textual data from social media.
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Provides a comprehensive overview of the social science research on the impact of social media on various aspects of society. Written by a computational social scientist, it explores topics such as fake news and the effects of advertising, offering insights into contemporary issues in social media. It's a good resource for understanding the broader implications of social media analysis.
Provides a comprehensive overview of social media analytics, including how to track, measure, and analyze social media activities to gain insights into user behavior, trends, and sentiment. It is particularly strong in its coverage of using social media analytics to improve marketing campaigns.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/tbh3pd/social
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Time
9 hours
Via
FutureLearn
Institution
Queensland University of Technology
Instructors
Jean Burgess
Kim Osman
Axel Bruns
Tim Highfield
Ehsan Dehghan
Edward Hurcombe
Silvia Montana
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