SJ5082 - Social Media and Data Journalism (2020/21)
|Module specification||Module approved to run in 2020/21|
|Module title||Social Media and Data Journalism|
|Module level||Intermediate (05)|
|Credit rating for module||15|
|School||School of Computing and Digital Media|
|Total study hours||150|
|Running in 2020/21||No instances running in the year|
Online and digital journalism skills are becoming essential for the industry and other media activities. New job roles are created for community managers and social media editors to increased vacancies for other new areas such as data journalism.
Anyone studying journalism needs to understand the challenges and opportunities posed by the data economy and the power of social media.
This module equips you with the learning to critically understand social media for audience feedback, community development, story development, and understanding analytics: how analytics are used to build audiences and how this data influences editorial decisions.
It will also teach the basics of data journalism, starting with spreadsheets and making sense of statistics, newsroom maths and storytelling using free visualisation tools. This module will introduce you to what you need to master in order for you to work in a professional capacity as a digital journalist.
This module will combine teaching the technical skills with an introduction to software tools – including understanding HTML embedding and writing for online and using free software such as Datawrapper, Tableau, TinEye, Hootsuite and more.
Some programming knowledge or blogging experience will be useful, as well as skills with graphics, but the main aim of the course will be to understand the principles of social media, what works for online and telling meaningful data journalism stories. Ethical concerns will be highlighted throughout, looking at verification and fake news, looking at web tools like webarchive.org, checking IDs and images.
The module will be assessed by timed in-class assessments, an investigative portfolio using sources, and entries to an online journal, moderated by tutors at the end of the teaching period
Prior learning requirements
Students will develop an understanding of how best to analyse and develop a social media strategy. LO3
They will realise that increase community engagement is the best way to grow your ‘patch’ as a journalist. They will understand what communicates best online for SEO and readers. LO5
They will also learn how to create compelling original journalism based on data and datasets. LO2,4
Since data journalism represents the convergence of a number of fields which are significant in their own right - from investigative research and statistics to design and programming –it crosses the fields of digital media and journalism. The idea of combining those skills to tell important stories is powerful - but also intimidating. The mining of social media for stories of public interest or interest to the public is a new challenge for journalists. LO1,5
The course will outline: LO2,3,5
● What works best online - web writing and SEO, understanding web metrics and other tracking analytics.
● Social media management and social curation.
● The key components of data journalism, finding stories in data, FOI and searching for stats
● Spreadsheets and newsroom maths
● Visualising data - from basic chart creation to advanced design and interactive
● Social media auditing and self-auditing, brand awareness
● An introduction to scraping and code
Journalists will produce work using the tools for the first assignment, which will be marked on proficiency in techniques.
Balance of independent study and scheduled teaching activity
Learning and teaching strategy will be based on an interactive model. For most of the 13 teaching weeks, a three-hourly session will require students to work with each other and individually on technical and newsgathering tasks.
They will also need to create their own recording techniques, devise their preferred visualisations, present independent research and ideas and contest information presented by staff and other students. They will need to practise at home, quite extensively.
Their final portfolios will display professional skills learned in class. These will be suitable for PDP.
In enhancement weeks, newsdays will allow a virtual professional environment to foster team-building and employability.
Reflection will be monitored on the class journal.
Students who read all the required texts, participate in all the class activities and complete the required assessments and assignments, should be able to:
1. Utilise the techniques and tools required for data news gathering and writing to a professionally and ethically acceptable level, working singly and collaboratively;
2. Write to length and to brief, working within different media and for different effects, creating a portfolio of work and displaying it across social media;
3. Analyse, develop and use in practice the data analysis skills needed to develop stories from a variety of sources, including recording, visualising and mashing up;
4. Present and originate stories in different formats and different modes, across different platforms;
5. Reflect upon and be able to explain the rationale for technical, ethical and professional choices.
Formative assessment will comprise short exercises and presentations to seminars and workshops. Formative feedback will also be given on draft portfolio items.
Summative assessment will comprise: one portfolio consisting of three pieces demonstrating data skills and story construction, timed in-class assessments demonstrating data skills and moderation by tutors of self-assessed contribution in class, monitored through a class journal.
The timed assessments will involve a data scraping exercise, which uses data from social media or other publicly available data to create a journalistic story, involving visualising and writing.
The portfolio will contain two short stories based on published data. The stories must be original, written in clear English and with at least two visual elements, like tables, maps, graphics or graphs. They can complement each other or contrast but must be about current journalistic topics. The third element is a rationale in which students must show how these would be spread through social media, the ethical considerations and their possible audience.
These elements represent what could make an important USP for students offering themselves in the workplace.
Portfolios must display the following evidence material:
1. Optimisation for SEO and good online writing:
All online writing must be optimised for SEO and web publication. Writing should be a compelling online read, formatted so that Google can understand it and your audience’s attention is held. You should also detail the dashboard work you to add keywords, tags, categories and summaries to make your writing relevant and findable. Summarise the outcome after publication (eg search engine results relative to similar/competing stories; other relevant metrics).
2) Content and social media for promotion: Writing does not exist in isolation: you should be writing your social updates to compel your audience to read. Work should also have an understanding of what works for an online audience and what the sell might be on a specific social platform.
3) Social media for networking and verification: Set out one example (a) demonstrating how you have used social media (and other suitable tools, where relevant) to identify a source and/or a news story; and (b) one example of how you have verified (as far as possible) editorially relevant information from social media sources.
4) Data or visual/interactive: Either: (a) explain how you found a story from data, including the steps taken to obtain, check, research, analyse and visualise or map the material. Or: (b) set out one example of visual, interactive storytelling that you created.
5) Legal and/or ethical issues – Note any legal and/or ethical issues that arise and/or need consideration, including how you approached/handled them and why they are important.
Familiarity with software is the most important reading/study
Felle, T., Mair, J. & Radcliffe, D. (2015) Data Journalism: Inside the global future. Abramis.
Gray, J., Bounegru, L. & Chambers, L. (2012) The Data Journalism Handbook. O’Reilly.
Vis F (2013) Twitter as a reporting tool for breaking news. Digital Journalism, 1(1), 27.
Free online tools
Websites: (all content)