Journalism – (noun) The occupation of reporting, writing, editing, photographing, or broadcasting news or of conducting any news organization as a business
This traditional definition of journalism (Dictionary.com http://bit.ly/dCdXBa) despite massive leaps forward in technology and attitude, still sums up exactly what the profession is about today: in short, getting the news out there.
Unfortunately, some are reluctant to accept these changes to the industry: old school hacks refusing to interact with readers online, newspapers not utilising video, radio stations limiting themselves to audio broadcast, whilst, behind them, there is an army of citizen reporters armed with iPhones, Youtube, Flickr, Audioboo and Bambuser ready to step in and take over the gatekeeping of the worlds news.
These are exciting times, and at the start of this educational trip into multimedia journalism, I expected to focus on video, with a brief (and required) nod towards to audio and Flash.
Little did I know.
The toughest challenge from the outset was finding inspiration for projects. As a working multimedia journalist, that decision would be handled by the News Editor, who would give you a brief and a deadline.
So, I decided to play the role of a working multimedia journalist. Switching on Sky News, I took the first story that interested me, and ran with it.
Jonny Dorey is a British student, currently missing whilst studying in the USA. At this point the story lacked data (i.e. dates and times) so a simple roll-over flash animation showing the various elements of the story seemed the best option as a starting point with this media.
Ideally, with more knowledge and artistic skill, the story would have benefited from something a little more intricate (along the lines of the BBC visualization of the Jean-Charles de Menezes shooting in London). This visualization is outstanding, with the image zooming in at each stage, and moving markers to show the relevant parties. However, the level of detail here was high due to the evidence revealed in court. At the time the information regarding Jonny Dorey was scant – although since then there have been suspected sightings of him – which would have worked well on a map based animation, as well as his possible route taken. Youtube appeals, photographs and other multimedia content could then be embedded into this map. A multimedia tool like this may have been useful in spreading the word about Jonny’s disappearance, and getting people involved in the search.
FESTIVAL MAP (link)
The Jonny Dorey project broke down the story and made it easier to digest, but Flash is also a useful tool for solving problems and aiding decision making.
Over the last few years the UK has become the centre of music festivals, with hundreds happening every summer. There are also dozens of websites that claim to centralise all this information (lineups, festival dates etc.), but none of them have managed it in a clear and visual way.
A Venn diagram would have worked well in showing the overlap between different bands playing the larger festivals, but, as yet, I am unable to find such a visualization tool that will achieve this. In retrospect, a clickable map showing which bands are playing where and when, was a lot more effective.
Featuring the 6 big festivals, and just the stage headliners (a manageable number, in order to get the project completed for publication), the map allows the user to click on a band’s name listed alongside, and points would flash on the UK map, with the festival name and date of appearance.
A second tier to this festival map would have been useful, where the user could click on the Festival point on the map and be shown all the bands playing, unfortunately the map was too crowded with “hotspots” and became unusable.
However, this information is constantly being updated and this does bring up the issues of maintaining and updating Flash sites. Would it be easy to ADD to the map, or would it make more sense to make a data map instead, with the information automatically pulled in from a feed?
The Maps Channels Events site handles events on a map excellently (even thought the interface is a little basic and ugly). You can search for a date, artist or venue – and it shows the location on a Google Map.
There is definitely scope to explore something like this, as festival websites are big business, and I could see one of the key sites, or music magazines, taking up this idea.
Glastonbury Festival is famously the UK’s largest music event, and I was keen to investigate how it has grown over the years, along with the price to attend (data acquired from official Glastonbury site)
Using Google Docs Spreadsheet and the ManyEyes visualization tool I created a scatter chart. ManyEyes has the limitations of not linking to live data, so if statistics change the data has to be re-pasted into the site but the choice of graphs and the interface made this a perfect tool for this project, and others.
I expected the chart to show a gradual increase both in capacity and ticket price, but it did flag up a drop in capacity after they took a break in 2006. It is this kind of anomaly that would work well illustrated in a timeline/chart mash-up – with landmarks in the festivals history (license issues, poor ticket sales, bad weather) – something akin to The Times Eating Chart, where the user rolls over the years, and sees the various developments.
There will be more on the issue of flawed data later in this document, but this chart does raise the issue of finances in charts over time in relation to Inflation. How does a £8 ticket in 1981 actually compare to a £185 priced ticket today? Does this make a mockery of statistics if the price is not converted into a standard “worth”? This issue has been seen recently with claims that Avatar is the highest grossing movie of all time.
More interesting was the comparison between the official capacity of the festival and the actual number of people attending. Glastonbury has had a long running battle with gatecrashers (or fence-hoppers) and as a news story this is an interesting set of data.
A bar chart suited this project, with the 2 capacity figures alongside each other, and showed just how dramatic the problem of “fence hopping” has been for the festival.
Unfortunately, actual capacity stats are hard to come by (as they are tricky to monitor) so “guestimated” figures were found in news reports (e.g. BBC, newspapers) and blogs, although I accept these figures are largely speculative and may be inaccurate. An FOI request has gone into Avon and Somerset Police, who should have some official estimated attendance figures.
Using estimated and reported data for a project like this also comes with a moral responsibility. Despite recent successful measures to prevent gatecrashers, according to some reports thousands of people are still getting into the site without paying. There is constant scrutiny of the management of the festival and I did feel uncomfortable publishing speculative figures that could be taken out of context by critics (including the local council who approve the license for the event).
However, there was definitely room here to investigate any correlation between the price of the ticket and the numbers of people trying to get in for free – are people driven to jump the fence as the price goes up?
Unfortunately I simply did not have enough data (9 years worth of unofficial capacity stats) to hand to make this work effectively and will retry it if my Freedom of Information Act application to Avon and Somerset Police is successful.
As a more personal project, and to test some other charts on ManyEyes, I decided to make use of the data from my ITunes player.
By cutting and pasting the relevant columns (“artist”, “song”, “genre” and “plays”) into a spreadsheet, and using the ManyEyes Bubble Chart visualization, there was an instant display of the most played genres.
“Alternative” was the largest category – whereas most of the music I listen would fall under rock, electronic or industrial.
Tweaking the data, switching genre for artist showed that it was a classification issue, not musical taste, which had completely distorted the data. Celldweller, an industrial artist, had been categorized as alternative. I spotted the problem as I know the subject, but what about data from an external source?
How can we always trust the classification of data is correct? Even the rawest of data has still been analyzed and gone through a personal “opinion” filter. There have been examples of crime stats being skewed by personal opinion (whether it’s at face value, from the PC attending the call, or the data builder designing the charts) or even simple geography boundaries.
IAN HUNTLEY ATTACK
The recent attack on Soham killer Ian Huntley earned some interesting reaction online, with such high emotions it seems the public are still happy to see to man come to harm.
Using a Google spreadsheet and the command (=importfeed(“http://search.twitter.com/search.atom?q=huntley”, “”, “”, 20), I searched Twitter for all the tweets mentioning “Huntley” (as opposed to “Ian Huntley”, which would have limited the search to the more formal tweets from news outlets etc. “Huntley” picked up the casual, public point of view)
This created a spreadsheet of the latest 15 tweets containing the word Huntley, which were then copies into Wordle in order to create a WordCloud. This was not a particularly useful or interesting experiment, as it only highlights which words have been used the most – i.e. “Huntley” and “prison” – the more emotive words were used in smaller numbers so were not significant on the cloud.
Instead I decided to analyse how the story was being covered in 2 very different newspapers, The Guardian and the Daily Mail.
Over the past weeks I have been trying and testing several data visualization tools (Tableau, Gliffy, Graphviz) but have been taken with ManyEyes for it’s variety of charts, including analysis of TEXT
Using the Word Tree visualization, I copied the articles to analyse how the documents were structured, and which words followed HUNTLEY in the text. The Guardian’s report followed Huntley with “convicted” “forced to fight for his life” “held at knifepoint” and several basic words whereas the Daily Mails article “was given privileges” “supposed to be under constant surveillance” “lured schoolgirls Holly and Jessica”. This text analysis is a useful tool for clearly seeing how the focus of a report is handled, especially, in this case, when the report is written from 2 different points of view.
Although initially reluctant to do any form of audio due to my radio background (and not wanting to stay within my field), I did decide to explore the world of audio slideshows.
There are several effective examples of this, and I was impressed by the ability to create emotion through slow moving images (e.g. Duckrabbits). However, I wasn’t personally interested in following the documentary style, instead looking into the possibility of enhancing something that would normally take a simple audio form – a music news bulletin.
With my background in radio I could quickly produce an audio bulletin, and spend the time learning about using images and transitions.
However, sourcing the images legally was of concern to me and whilst images on Flickr via CreativeCommons – is an option, most of the pictures were taken at live shows from a distance, and were not suitable for this project.
Stock photograph websites do not carry celebrity shots and official press shots are hard to come by if their star is in the news for the wrong reasons.
Unfortunately it came back to a simple Google Image search and making use of the relevant pictures that provided.
The images had to be relatively close-up, of good quality and should supplement the story. For example the image of Pete Doherty with the policeman and Damon Albarn with the cigarette were obvious choices, considering the subject matter.
As an editor, Windows Movie Maker offers a range of movement and transition options for the images. Movement over and between the pictures added to the story – for example, zooming in on the eyes of Robin Whitehead, the heiress and filmmaker found dead in a London flat. This gave the impression of sadness and tragedy. There was also humour by using pictures to highlight the fact that the lead singer of Killswitch Engage has the same name as 80’s pop star Howard Jones.
This process took around an hour and a half in total, from writing the bulletin to having finished uploaded piece.
I would like to try to bring more humour into the report, along the lines of Rocketboom, otherwise this will simply be mimicking TV 60 second news style report, with images instead of video.
I would very much like to pursue this project on a regular basis (maybe even daily) but without access to good quality photographs legally, I do not believe it is possible.