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Wrapping it all up

Listen to Dr. Mathei as he summarizes the learning from this course.
Social media can tell us what people do or do not. What they feel, what they hated and how much their networks of support contribute to their thoughts and actions. I mentioned earlier our study about people’s reaction to Hurricane Sandy. We looked at over 40,000 tweets and we learned that, first of all, people tended to move away from danger. We did this by calculating the average place of their location at the beginning of the storm and comparing it to the average value of their location at the end. This map shows how the people who tweeted about Sandy moved inland and away from the path of the hurricane.
Moreover, we found out that the people who talked a lot about the storm and who expressed that interest in the latest news about it, were more likely to go out during the storm, exposing themselves to more danger. Sometimes a bit of reflection and distancing about an emergency situation can make you safer. Finally, we found that those that had more friends were more likely to stay away from danger. Could it be that a broader network of friends can act as an early warning system feeding you the needed information to stay safe? Social media analytics is, to a certain degree, alchemy.
The goal of alchemy was to turn one thing, usually of less value, into another, usually very valuable, such as lead into gold. Social media analystics turns people’s random thoughts, musings, words, pictures, and the links they stumble upon into actionable information. This is done by the magic of the tabular format, rows in a table are cases or things to be analyzed, tweets, posts, users. The columns are the characteristics, number of likes, favorites, etc. More important, the column’s characteristics are derived from behaviors. A like is the product of liking, it implies approval or support. The question that becomes, why did this person liked this tweet?
We find the answer to this question by scanning all the those that like social media content the same way and so on. Social media analytics isn’t the end about simplifying and empowering, it gives you the power to comprehend at a glance what trends and common characteristics across people and types of content emerge where and for what reason. It is compared to other forms of data collection cheaper. At least for unit of information and easier to collect. However, the content is not always of even quality. Anyone with a computer can create an online presence.
Some are there for the purpose to pollute the online medium, spam, conspiracy theories or simple idle thoughts make it hard to figure out what is good and what is bad. Sometime we do not even know if that stuff is human generated or not. In a word, for each benefit we need to look out for potential difficulties. Yet, social media analysis promises much and can give us just as much.
In these three weeks, we have seen how social media analytics is like alchemy, turning something of lesser value (social media data) into something of greater value (business intelligence and actionable insights) that can help organisations make better decisions.
The opening example of Superstorm Sandy demonstrated that human activity on social media generated large volumes of data that became very valuable when interpreted (like keeping people away from danger). Analysts used spreadsheets to categorise and interpret the data and were able to extract actionable insights from the thousands of tweets to develop timely intelligence.
Now, you have successfully learned that there are both opportunities and limitations of using data from the social media that your business owns. You are also now able to meaningfully reflect and strategise on how to design and use social media analytics to interpret data and draw out actionable insights.
Congratulations on completing this course! You now know how social and digital media information can be turned into business intelligence!
This is the first course in the program, Social and Digital Media Analytics for Business Communication. Within the program, you will further explore how to identify and use social media as a source of business intelligence and behavioral analytics, how to quantify human behavior, how to engage in simple social media data mining, and how to interpret the findings into data-driven recommendations for an organization. The program will launch in 2019. Course topics include:
  • Building a Research Plan to Analyze Social Media
  • Leveraging Data through Owned Media
  • Increasing Online Presence through Earned Media
  • Promoting the Message through Paid Media
  • Advanced Analytics – Extracting and Leveraging “Listening Data”
  • Assessment – Putting It All Together
We hope that you will continue to reflect on what you have learned and continue to develop the skills you have gained. Feel free to leave any comments.
Students who upgrade and complete the first 6 courses in the program will be eligible to take the final assessment course. Upon completion of the assessment course, students that apply and are admitted to Purdue’s online Master of Science in Communication program can submit to have their completed FutureLearn program count as 3 credits towards the degree.
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Digital Media Analytics: Introduction

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