Social Networks and Data Journalism Chapter 10 Mantie Reid Pace University Social Networks and Data Journalism Chapter 10 Mantie Reid 11/8/2018 Doing Data Science - Stright Talk from the Front Line

Social Networks Analysis at Morning Analytics The emergence of online social networks – Facebook, LinkedIn, Twitter, and Google+ creates a rich source of data which opens many research problems both from social science and quantitative/technical viewpoint Kelly wants to understand how people come together and when they do, what their impact is on politics and public policy. Sees math, statistics, computer science (Including machine learning) as tools he needs to use Data Journalism: Constructing stories that can be told from social networking data Expertise lies in visualization combined with drawing conclusions from those visualizations C. O’Neil, R. Schutt, “ Doing Data Science – Straight Talk From The Frontline”, 2013 O’Reilly Media Inc., PP. 253-54 11/8/2018 Doing Data Science - Stright Talk from the Front Line

Case-Attribute Data versus Social Network Data Case-attribute refers to how you normally see people feed models with various “cases,” which can refer to people or events – each of which have various “attributes,” which can refer to age, or operating systems, or search histories. Why network analysis is sometimes superior to case attribute data analysis; ex: The federal government spent money to poll people in Afghanistan. The idea was to see what citizens want in order to anticipate what’s going to happen in the future. Kelly: What will happen isn’t a simple function of what individuals think; instead, it’s a question of who has the power and what they think C. O’Neil, R. Schutt, “ Doing Data Science – Straight Talk From The Frontline”, 2013 O’Reilly Media Inc., PP. 254-256 11/8/2018 Doing Data Science - Stright Talk from the Front Line

Case-Attribute Data versus Social Network Data Imagine going back in time, conducting a scientific poll of the citizenry of Europe in 1750 to determine the future of politics If you knew what you were doing , you’d be looking at who was marrying whom among the royalty Kelly claims that the world is a network much like it’s a bunch of cases with attributes. If you only understand how individual behave, how do you tie things together C. O’Neil, R. Schutt, “ Doing Data Science – Straight Talk From The Frontline”, 2013 O’Reilly Media Inc., PP. 256-255 11/8/2018 Doing Data Science - Stright Talk from the Front Line

Doing Data Science - Stright Talk from the Front Line Thought Experiment Predict the future political situation of Egypt. What kinds of political parties will there be? What is the country of Egypt going to look like in 5, 10, or 20 years? You have access to exactly two of the following datasets for all Egyptians: the Facebook or Twitter network, a complete record of who went to school with who, the text or phone records of everyone, everyone’s addresses, or the network data on members of all formal political organizations and private companies. Consider changing the standard direction of your thinking What can we learn from this or that data source? What would it mean to predict politics in a society? What kind of data would you need to do that? Figure out the questions first and then look for data to help answer them. C. O’Neil, R. Schutt, “ Doing Data Science – Straight Talk From The Frontline”, 2013 O’Reilly Media Inc., PP. 259- 260 11/8/2018 Doing Data Science - Stright Talk from the Front Line

Morningside Analytics Example of the Arabic blogosphere 11/8/2018

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Doing Data Science - Stright Talk from the Front Line Data Journalism Practice of Data Journalism is divided into various fields: Graphics Vs interactive Feature Research Database engineers Crawlers Software Developers Domain Expert Writers C. O’Neil, R. Schutt, “ Doing Data Science – Straight Talk From The Frontline”, 2013 O’Reilly Media Inc., PP. 270 11/8/2018 Doing Data Science - Stright Talk from the Front Line

Writing Technical Journalism: Advice from an Expert Data Journalism involved lots of Data visualization; it is a fast way of describing the bottom line of a dataset Statistics inspired you to write things about the world E.g., the average person on Twitter is a woman with 250 followers, but the median person has 0 followers – the data is clearly skewed; that’s an inspiration right there for a story! The fundamental skill is translation: taking complicated stories and deriving meaning that readers will understand They also needs to anticipate questions and turn them into quantitative experiments and answer them persuasively Don’t have a strong thesis before you interview the experts Go in with a loose idea of what you are searching for and be willing to change your mind and pivot if the experts lead you in a new and interesting direction C. O’Neil, R. Schutt, “ Doing Data Science – Straight Talk From The Frontline”, 2013 O’Reilly Media Inc., PP. 270-271 11/8/2018 Doing Data Science - Stright Talk from the Front Line