Tag Archives: crowdsourcing

Announcing Help Me Investigate the Olympics

My crowdsourced investigative journalism project Help Me Investigate has launched a fourth specialist site: Help Me Investigate the Olympics.

The site is being run by a colleague of mine from Birmingham City University, Jennifer Jones, as part of a project we’re working on which sees students at BCU and other universities connecting to wider online networks in investigating Olympics-related questions.

Jennifer knows those networks particularly well as the coordinator for #media2012, web editor and staff editor for Culture @ the Olympics. She is also writing her PhD on Social Media, Activism and the Olympic Games at the University of the West of Scotland.

If you want to contribute to the site or related investigations, get in touch in the comments or via Olympics@helpmeinvestigate.com

A case study in crowdsourcing investigative journalism part 7: Conclusions

In the final part of the research underpinning a new Help Me Investigate project I explore the qualities that successful crowdsourcing investigations shared. Previous parts are linked below:

Conclusions

Looking at the reasons that users of the site as a whole gave for not contributing to an investigation, the majority attributed this to ‘not having enough time’. Although at least one interviewee, in contrast, highlighted the simplicity and ease of contributing, it needs to be as easy and simple as possible for users to contribute (or appear to be) in order to lower the perception of effort and time needed.

Notably, the second biggest reason for not contributing was a ‘lack of personal connection with an investigation’, demonstrating the importance of the individual and social dimension of crowdsourcing. Likewise, a ‘personal interest in the issue’ was the single largest factor in someone contributing. A ‘Why should I contribute?’ feature on crowdsourcing projects may be worth considering.

Others mentioned the social dimension of crowdsourcing – the “sense of being involved in something together” – what Jenkins (2006, p244) would refer to as “consumption as a networked practice”, a motivation also identified by Yochai Benkler in his work on networks (2006). Looking at non-financial motivations behind people contributing their time to online projects, he refers to “socio-psychological reward”. He also identifies the importance of “hedonic personal gratification”. In other words, fun.

Although positive feedback formed part of the design of the site, no consideration was paid to negative feedback: users being made aware of when they were not succeeding. This element also appears to be absent from game mechanics in other crowdsourcing experiments such as The Guardian’s MPs’ expenses app.

While it is easy to talk about “Failure for free”, more could be done to identify and support failing investigations. A monthly update feature that would remind users of recent activity and – more importantly – the lack of activity might help here. The investigators in a group might be asked whether they wish to terminate the investigation in those cases, emphasising their responsibility for its progress and helping ‘clean up’ the investigations listed on the first page of the site.

However, there is also a danger in interfering too much in reducing failure. This is a natural instinct, and the establishment of a reasonable ‘success rate’ at the outset – based on the literature around crowdsourcing – helps to counter this. That was part of the design of Help Me Investigate: it was the 1-5% of questions that gained traction that would be the focus of the site. One analogy is a news conference where members throw out ideas – only a few are chosen for investment of time and energy, the rest ‘fail’.

It is the management of that tension between interfering to ensure everything succeeds (and so removing the incentive for users to be self-motivated) and not interfering at all (leaving users feeling unsupported and unmotivated) that is likely to be the key to a successful crowdsourcing project. More than a year into the project, this tension was still being negotiated.

In summing up the research into Help Me Investigate it is possible to identify five qualities which successful investigations shared: ‘Alpha users’ (highly active, who drove investigations forward); modularity (the ability to break down a large investigation into smaller discrete elements); public-ness (the ability for others to find out about an investigation); feedback (game mechanics and the pleasure of using the site); and diversity of users.

Relating these findings to other research into crowdsourcing more generally it is possible to make broader generalisations regarding how future projects might be best organised. Leadbeater (2008, p68), for example, identifies five key principles of successful collaborative projects, summed up as ‘Core’ (directly comparable to the need for alpha users identified in this research); ‘Contribute’ (large numbers, comparable to public-ness); ‘Connect’ (diversity); ‘Collaborate’ (self governance – relating indirectly to modularity); and ‘Create’ (creative pleasure – relating indirectly to feedback). Similar qualities are also identified by US investigative reporter and Knight fellow Wendy Norris in her experiments with crowdsourcing (Lavrusik, 2010).

The most notable connections here are the indirect ones. While the technology of Help Me Investigate allowed for modularity, for example, the community structure was rather flat. Leadbeater’s research (2008) and that of Lih (2009) into the development of Wikipedia and Tsui (2010, PDF) into Global Voices indicate that ‘modularity’ may be part of a wider need for ‘structure’. Conversely ‘feedback’ provides a specific, practical way for crowdsourcing projects to address users’ need for creative pleasure.

As Help Me Investigate reached its 18th month a number of changes were made to test these ideas: the code was released as open source, effectively crowdsourcing the technology itself, and a strategy was adopted to recruit niche community managers who could build expertise in particular fields, along with an advisory board that was similarly diverse. The Help Me Investigate design was replicated in a plugin which would allow anyone running a self-hosted WordPress blog to manage their own version of the site.

This separation of technology from community was a key learning outcome of the project. While the site had solved some of the technical challenges of crowdsourcing and identified the qualities of successful crowdsourced investigation, it was clear that the biggest challenge lay in connecting the increasingly networked communities that wanted to investigate public interest issues – and in a way that was both sustainable and scalable beyond the level of individual investigations.

 

References

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  38. Weinberger, David (2002) Small Pieces, Loosely Joined, New York: Basic Books

What made the crowdsourcing successful? A case study in crowdsourcing investigative journalism part 6

In the penultimate part of the serialisation of research underpinning a new Help Me Investigate project I explore the qualities that successful crowdsourcing investigations shared. Previous parts are linked below:

What made the crowdsourcing successful?

Clearly, a distinction should be made between what made the investigation successful as a series of outcomes, and what made crowdsourcing successful as a method for investigative reporting. This section concerns itself with the latter.

What made the community gather, and continue to return? One hypothesis was that the nature of the investigation provided a natural cue to interested parties – The London Weekly was published on Fridays and Saturdays and there was a build up of expectation to see if a new issue would indeed appear.

The data, however, did not support this hypothesis. There was indeed a rhythm but it did not correlate to the date of publication. Wednesdays were the most popular day for people contributing to the investigation.

Upon further investigation a possible explanation was found: one of the investigation’s ‘alpha’ contributors – James Ball – had set himself a task to blog about the investigation every week. His blog posts appeared on a Wednesday.

That this turned out to be a significant factor in driving activity suggests one important lesson: talking publicly and regularly about the investigation’s progress is key to its activity and success.

This data was backed up from the interviews. One respondent mentioned the “weekly cue” explicitly. And Jon Hickman’s research also identified that investigation activity related to “events and interventions. Leadership, especially by staffers, and tasking appeared to be the main drivers of activity within the investigation.” (2010, p10)

He breaks down activity on the site into three ‘acts’, although their relationship to the success of the investigation is not explored further:

  • ‘Brainstorm’ (an initial flurry of activity, much of which is focused on scoping the investigation and recruiting)
  • ‘Consolidation’ (activity is driven by new information)
  • ‘Long tail’ (intermittent caretaker activity, such as supportive comments or occasional updates)

Networked utility

Hickman describes the site as a “centralised sub-network that suits a specific activity” (2010, p12). Importantly, this sub-network forms part of a larger ‘network of networks’ which involves spaces such as users’ blogs, Twitter, Facebook, email and other platforms and channels.

“And yet Help Me Investigate still provided a useful space for them to work within; investigators and staffers feel that the website facilitates investigation in a way that their other social media tools could not:

““It adds the structure and the knowledge base; the challenges, integration with ‘what do they know’ ability to pose questions allows groups to structure an investigation logically and facilitates collaboration.” (Interview with investigator)” (Hickman, 2010, p12)

In the London Weekly investigation the site also helped keep track of a number of discussions taking place around the web. Having been born from a discussion on Twitter, further conversations on Twitter resulted in further people signing up, along with comments threads and other online discussion. This fit the way the site was designed culturally – to be part of a network rather than asking people to do everything on-site.

The presence of ‘alpha’ users like James and Judith was crucial in driving activity on the site – a pattern observed in other successful investigations. They picked up the threads contributed by others and not only wove them together into a coherent narrative that allowed others to enter more easily, but also set the new challenges that provided ways for people to contribute. The fact that they brought with them a strong social network presence is probably also a factor – but one that needs further research.

The site had been designed to emphasise the role of the user in driving investigations. The agenda is not owned by a central publisher, but by the person posing the question – and therefore the responsibility is theirs as well. This cultural hurdle – towards acknowledging personal power and responsibility – may be the biggest one that the site has to address, and the offer of “failure for free” (Shirky, 2008), allowing users to learn what works and what doesn’t, may support that.

The fact that crowdsourcing worked well for the investigation is worth noting, as it could be broken down into separate parts and paths – most of which could be completed online: “Where does this claim come from?” “Can you find out about this person?” “What can you discover about this company?”. One person, for example, used Google Streetview to establish that the registered address of the company was a postbox. Other investigations that are less easily broken down may be less suitable for crowdsourcing – or require more effort to ensure success.

Momentum and direction

A regular supply of updates provided the investigation with momentum. The accumulation of discoveries provided valuable feedback to users, who then returned for more. In his book on Wikipedia, Andrew Lih (2009 p82) notes a similar pattern – ‘stigmergy’ – that is observed in the natural world: “The situation in which the product of previous work, rather than direct communication [induces and directs] additional labour”. An investigation without these ‘small pieces, loosely joined’ (Weinberger, 2002) might not suit crowdsourcing so well.

Hickman’s interviews with participants in the Birmingham council website investigation found a feeling of the investigation being communally owned and led:

“Certain members were good at driving the investigation forward, helping decide on what to do next, but it did not feel like anyone was in charge as such.”

“I’d say HMI had pivital role in keeping us together and focused but it felt owned by everyone.” (Hickman 2010, p10)

One problem, however, was that the number of diverging paths led to a range of potential avenues of enquiry. In the end, although the core questions were answered (was the publication a hoax and what were the bases for their claims) the investigation raised many more questions. These remained largely unanswered once the majority of users felt that their questions had been answered. As in a traditional investigation, there came a point at which those involved had to make a judgement whether they wished to invest any more time in it.

Finally, the investigation benefited from a diverse group of contributors who contributed specialist knowledge or access. Some physically visited stations where the newspaper was claiming distribution to see how many copies were being handed out. Others used advanced search techniques to track down details on the people involved and the claims being made, or to make contact with people who had had previous experiences with those behind the newspaper. The visibility of the investigation online also led to more than one ‘whistleblower’ approach providing inside information, which was not published on the site but resulted in new challenges being set.

The final part of this series outlines some conclusions to be taken from the project, and where it plans to go next.

What are the characteristics of a crowdsourced investigation? A case study in crowdsourcing investigative journalism part 5

Continuing the serialisation of the research underpinning a new Help Me Investigate project, in this fifth part I explore the characteristics of crowdsourcing outlined in the literature. Previous parts are linked below:

What are the characteristics of a crowdsourced investigation?

Tapscott and Williams (2006, p269) explore a range of new models of collaboration facilitated by online networks across a range of industries. These include:

  • Peer producers creating “products made of bits – from operating systems to encyclopedias”
  • “Ideagoras … a global marketplace of ideas, innovations and uniquely qualified minds”
  • Prosumer – ‘professional consumer’ – communities which can produce value if given the right tools by companies
  • Collaborative science (“The New Alexandrians”)
  • Platforms for participation
  • “Global plant floors” – physical production lines split across countries
  • Wiki workplaces which cut across organisational hierarchies

Most of these innovations have not touched the news industry, and some – such as platforms for participation – are used in publishing, but rarely in news production itself (an exception here can be made for a few magazine communities, such as Reed Business Information’s Farmer’s Weekly).

Examples of explicitly crowdsourced journalism can be broadly classified into two types. The first – closest to the ‘Global plant floors’ described above – can be described as the ‘Mechanical Turk’ model (after the Amazon-owned web service that allows you to offer piecemeal payment for repetitive work). This approach tends to involve large numbers of individuals performing small, similar tasks. Examples from journalism would include The Guardian’s experiment with inviting users to classify MPs’ expenses in order to find possible stories, or the pet food bloggers inviting users to add details of affected pets to their database.

The second type – closest to the ‘peer producers’ model – can be described as the ‘Wisdom of Crowds’ approach (after James Surowiecki’s 2005 book of the same name). This approach tends to involve smaller numbers of users performing discrete tasks that rely on a particular expertise. It follows the creed of open source software development, often referred to as Linus’ Law, which states that: “Given enough eyeballs, all bugs are shallow” (Raymond, 1999). The Florida News Press example given above fits into this category, relying as it did on users with specific knowledge (such as engineering or accounting) or access. Another example – based explicitly on examples in Surowiecki’s book – is that of an experiment by The Guardian’s Charles Arthur to predict the specifications of Apple’s rumoured tablet (Arthur, 2010). Over 10,000 users voted on 13 questions, correctly predicting its name, screen size, colour, network and other specifications – but getting other specifications, such as its price, wrong.

Help Me Investigate fits into the ‘Wisdom of Crowds’ category: rather than requiring users to complete identical tasks, the technology splits investigations into different ‘challenges’. Users are invited to tag themselves so that it is easier to locate users with particular expertise (tagged ‘FOI’ or ‘lawyer’ for example) or in a particular location, and many investigations include a challenge to ‘invite an expert’ from a particular area that is not represented in the group of users.

Some elements of Tapscott and Williams’s list can also be related to Help Me Investigate’s processes: for example, the site itself was a ‘platform for participation’ which allowed users from different professions to collaborate without any organisational hierarchy. There was an ‘ideagora’ for suggesting ways of investigating, and the resulting stories were examples of peer production.

One of the first things the research analysed was whether the investigation data matched up to patterns observed elsewhere in crowdsourcing and online activity. An analysis of the number of actions by each user, for example, showed a clear ‘power law’ distribution, where a minority of users accounted for the majority of activity.

This power law, however, did not translate into a breakdown approaching the 90-9-1 ‘law of participation inequality’ observed by Jakob Nielsen (2006). Instead, the balance between those who made a couple of contributions (normally the 9% of the 90-9-1 split) and those who made none (the 90%) was roughly equal. This may have been because the design of the site meant it was not possible to ‘lurk’ without being a member of the site already, or being invited and signing up. Adding in data on those looking at the investigation page who were not members may shed further light on this.

In Jon Hickman’s ethnography of a different investigation (into the project to deliver a new website for Birmingham City Council) he found a similar pattern: of the 32 ‘investigators’, thirteen did nothing more than join the investigation. Others provided “occasional or one-off contributions”, and a few were “prolific” (Hickman, 2010, p10). Rather than being an indication of absence, however, Hickman notes the literature on lurking that suggests it provides an opportunity for informal learning. He identifies support for this in his interviews with lurkers on the site:

“One lurker was a key technical member of the BCC DIY collective: the narrative within Help Me Investigate suggested a low level of engagement with the process and yet this investigator was actually quite prominent in terms of their activism; the lurker was producing pragmatic outcomes and responses to the investigation, although he produced no research for the project. On a similar note, several of the BCC DIY activists were neither active nor lurking within Help Me Investigate. For example, one activist’s account of BCC DIY shows awareness of, and engagement with, the connection between the activist activity and the investigation, even though he is not an active member of the investigation within Help Me Investigate.” (Hickman, 2010, p17)

In the next part I explore what qualities made for successful crowdsourcing in the specific instance of Help Me Investigate.

A case study in crowdsourcing investigative journalism (part 4): The London Weekly

Continuing the serialisation of the research underpinning a new Help Me Investigate project, in this fourth part I describe how one particular investigation took shape. Previous parts are linked below:

Case study: the London Weekly investigation

In early 2010 Andy Brightwell and I conducted some research into one particular successful investigation on the site. The objective was to identify what had made the investigation successful – and how (or if) those conditions might be replicated for other investigations both on the site and elsewhere online.

The investigation chosen for the case study was ‘What do you know about The London Weekly?’ – an investigation into a free newspaper that was, the owners claimed (part of the investigation was to establish if the claim was a hoax), about to launch in London.

The people behind The London Weekly had made a number of claims about planned circulation, staffing and investment which went unchallenged in specialist media. Journalists Martin Stabe, James Ball and Judith Townend, however, wanted to dig deeper. So, after an exchange on Twitter, Judith logged onto Help Me Investigate and started an investigation.

A month later members of the investigation (most of whom were non-journalists) had unearthed a wealth of detail about the people behind The London Weekly and the facts behind their claims. Some of the information was reported in MediaWeek and The Guardian podcast Media Talk; some formed the basis for posts on James Ball’s blog, Journalism.co.uk and the Online Journalism Blog. Some has, for legal reasons, remained unpublished.

Methodology

Andrew Brightwell conducted a number of semi-structured interviews with contributors to the investigation. The sample was randomly selected but representative of the mix of contributors, who were categorised as either ‘alpha’ contributors (over 6 contributions), ‘active’ (2-6 contributions) and ‘lurkers’ (whose only contribution was to join the investigation). These interviews formed the qualitative basis for the research.

Complementing this data was quantitative information about users of the site as a whole. This was taken from two user surveys – one conducted when the site was three months’ old and another at 12 months – and analysis of analytics taken from the investigation (such as numbers and types of actions, frequency, etc.)

In the next part I explore some of the characteristics of a crowdsourced investigation and how these relate to the wider literature around crowdsourcing in general.

Crowdsourcing investigative journalism: a case study (part 3)

Continuing the serialisation of the research underpinning a new Help Me Investigate project, in this third part I describe how the focus of the site was shaped by the interests of its users and staff, and how site functionality was changed to react to user needs. I also identify some areas where the site could have been further developed and improved. (Part 1 is available here; Part 2 is here)

Reflections on the proof of concept phase

By the end of the 12 week proof of concept phase the site had also completed a number of investigations that were not ‘headline-makers’ but fulfilled the objective of informing users: in particular ‘Why is a new bus company allowed on an existing route with same number, but higher prices?’; ‘What is the tracking process for petitions handed in to Birmingham City Council?’ and ‘The DVLA and misrepresented number plates’

The site had also unearthed some promising information that could provide the basis for more stories, such as Birmingham City Council receiving over £160,000 in payments for vehicle removals; and ‘Which councils in the UK (that use Civil Enforcement) make the most from parking tickets?’ (as a byproduct, this also unearthed how well different councils responded to Freedom of Information requests#)

A number of news organisations expressed an interest in working with the site, but practical contributions to the site took place largely at an individual rather than organisational level. Journalist Tom Scotney, who was involved in one of the investigations, commented: “Get it right and you’re becoming part of an investigative team that’s bigger, more diverse and more skilled than any newsroom could ever be” (Scotney, 2009, n.p.) – but it was becoming clear that most journalists were not culturally prepared – or had the time – to engage with the site unless there was a story ‘ready made’ for them to use. Once there were stories to be had, however, they contributed a valuable role in writing those stories up, obtaining official reactions, and spreading visibility.

After 12 weeks the site had around 275 users (whose backgrounds ranged from journalism and web development to locally active citizens) and 71 investigations, exceeding project targets. It is difficult to measure ‘success’ or ‘failure’ but at least eight investigations had resulted in coherent stories, representing a success rate of at least 11%: the target figure before launch had been 1-5%. That figure rose to around 21% if other promising investigations were included, and the sample included recently initiated investigations which were yet to get off the ground.

‘Success’ was an interesting metric which deserves further elaboration. In his reflection on The Guardian’s crowdsourcing experiment, for example, developer Martin Belam (2011a, n.p.) noted a tendency to evaluate success “not purely editorially, but with a technology mindset in terms of the ‘100% – Achievement unlocked!’ games mechanic.”. In other words, success might be measured in terms of degrees of ‘completion’ rather than results.

In contrast, the newspaper’s journalist Paul Lewis saw success in terms of something other than pure percentages: getting 27,000 people to look at expense claims was, he felt, a successful outcome, regardless of the percentage of claims that those represented. And BBC Special Reports Editor Bella Hurrell – who oversaw a similar but less ambitious crowdsourcing project on the same subject on the broadcaster’s website, felt that they had also succeeded in genuine ‘public service journalism’ in the process (personal interview).

A third measure of success is noted by Belam – that of implementation and iteration (being able to improve the service based on how it is used):

“It demonstrated that as a team our tech guys could, in the space of around a week, get an application deployed into the cloud but appear integrated into our site, using a technology stack that was not our regular infrastructure.

“Secondly, it showed that as a business we could bring people together from editorial, design, technology and QA to deliver a rapid turnaround project in a multi-disciplinary way, based on a topical news story.

“And thirdly, we learned from and improved upon it.“ (Belam, 2010, n.p.)

A percentage ‘success’ rate of Help Me Investigate, then, represents a similar, ‘game-oriented’ perspective on the site, and it is important to draw on other frameworks to measure its success.

For example, it was clear that the site did very well in producing raw material for ‘journalism’, but it was less successful in generating more general civic information such as how to find out who owned a piece of land. Returning to the ideas of Actor-Network Theory outlined above, the behaviour of two principal actors – and one investigation – had a particular influence on this, and how the site more generally developed over time. Site user Neil Houston was an early adopter of the site and one of its heaviest contributors. His interest in interrogating data helped shape the path of many of the site’s most active investigations, which in turn set the editorial ‘tone’ of the site. This attracted users with similar interests to Neil, but may have discouraged others who did not – further research would be needed to establish this.

Likewise, while Birmingham City Council staff contributed to the site in its earliest days, when the council became the subject of an investigation staff’s involvement was actively discouraged (personal interview with contributor). This left the site short of particular expertise in answering civic questions.

At least one user commented that the site was very ‘FOI [Freedom Of Information request]-heavy’ and risked excluding users interested in different types of investigations, or who saw Freedom of Information requests as too difficult for them. This could be traced directly to the appointment of Heather Brooke as the site’s support journalist. Heather is a leading Freedom of Information activist and user of FOI requests: this was an enormous strength in supporting relevant investigations but it should also be recognised how that served to set the editorial tone of the site.

This narrowing of tone was addressed by bringing in a second support journalist with a consumer background: Colin Meek. There was also a strategic shift in community management which involved actively involving users with other investigations. As more users came onto the site these broadened into consumer, property and legal areas.

However, a further ‘actor’ then came into play: the legal and insurance systems. Due to the end of proof of concept funding and the associated legal insurance the team had to close investigations unrelated to the public sector as they left the site most vulnerable legally.

A final example of Actor-Network Theory in action was a difference between the intentions of the site designers and its users. The founders wanted Help Me Investigate to be a place for consensus, not discussion, but it was quickly apparent users did not want to have to go elsewhere to have their discussions. Users needed to – and did – have conversations around the updates that they posted.

The initial challenge-and-result model (breaking investigations down into challenges with entry fields for the subsequent results, which were required to include a link to the source of their information) was therefore changed very early on to challenge-and-update: people could now update without a link, simply to make a point about a previous result, or to explain their efforts in failing to obtain a result.

One of the challenges least likely to be accepted by users was to ‘Write the story up’. It seemed that those who knew the investigation had no need to write it up: the story existed in their heads. Instead it was either site staff or professional journalists who would normally write up the results. Similarly, when an investigation was complete, it required site staff to update the investigation description to include a link to any write-up. There was no evidence of a desire from users to ‘be a journalist’. Indeed, the overriding objective appeared rather to ‘be a citizen’.

In contrast, a challenge to write ‘the story so far’ seemed more appealing in investigations that had gathered data but no resolution as yet. The site founders underestimated the need for narrative in designing a site that allowed users to join investigations while they were in progress.

As was to be expected with a ‘proof of concept’ site (one testing whether an idea could work), there were a number of areas of frustration in the limitations of the site – and identification of areas of opportunity. When looking to crowdfund small amounts for an investigation, for example, there were no third party tools available that would allow this without going through a nonprofit organisation. And when an investigation involved a large crowdsourcing operation the connection to activity conducted on other platforms needed to be stronger so users could more easily see what needed doing (e.g. a live feed of changes to a Google spreadsheet, or documents bookmarked using Delicious).

Finally investigations often evolved into new questions but had to stay with an old title or risk losing the team and resources that had been built up. The option to ‘export’ an investigation team and resources into a fresh question/investigation was one possible future solution.

‘Failure for free’ was part of the design of the site in order to allow investigations to succeed on the efforts of its members rather than as a result of any top-down editorial agenda – although naturally journalist users would concentrate their efforts on the most newsworthy investigations. In practice it was hard to ‘let failure happen’, especially when almost all investigations had some public interest value.

Although the failure itself was not an issue (and indeed the failure rate lower than expected), a ‘safety net’ was needed that would more proactively suggest ways investigators could make their investigation a success, including features such as investigation ‘mentors’ who could pass on their experience; ‘expiry dates’ on challenges with reminders; improved ability to find other investigators with relevant skills or experience; a ‘sandbox’ investigation for new users to find their feet; and developing a metric to identify successful and failing investigations.

Communication was central to successful investigations and two areas required more attention: staff time in pursuing communication with users; and technical infrastructure to automate and facilitate communication (such as alerts to new updates or the ability to mail all investigation members)

The much-feared legal issues threatened by the site did not particularly materialise. Out of over 70 investigations in the first 12 weeks, only four needed rephrasing to avoid being potentially libellous. Two involved minor tweaks; the other two were more significant, partly because of a related need for clarity in the question.

Individual updates within investigations, which were post-moderated, presented even less of a legal problem. Only two updates were referred for legal advice, and only one of those rephrased. One was flagged and removed because it was ‘flamey’ and did not contribute to the investigation.

There was a lack of involvement by users across investigations. Users tended to stick to their own investigation and the idea of ‘helping another so they help you’ did not take root. Further research is needed to see if there was a power law distribution at work here – often seen on the internet – of a few people being involved in lots of investigations, most being involved in one, and a steep upward curve between.

In the next part I look at one particular investigation in an attempt to identify the qualities that made it successful.

If you want to get involved in the latest Help Me Investigate project, get in touch on paul@helpmeinvestigate.com

Crowdsourcing investigative journalism: a case study (part 2)

Continuing the serialisation of the research underpinning a new Help Me Investigate project, in this second part I describe the basis for the way that the original site was constructed – and the experiences of its first few months. (Part 1 is available here)

Building the site

By 2008 two members had joined the Help Me Investigate team: web developer Stef Lewandowski and community media specialist Nick Booth, and the project won funding that year from Channel 4’s 4iP fund and regional development agency Screen West Midlands.

Two part time members of ‘staff’ were recruited to work one day per week for the site throughout the 12 week funded ‘proof of concept’ period: a support journalist and a community manager.

Site construction began in April 2009, and began by expanding on the four target user profiles in the bid document to outline 12 profiles of users who might be attracted to the site, identifying what they would want to do with the site and how the design might facilitate that – or prevent it (as in the case, for example, of users who might want to hijack or hoax the site).

This was followed by rapid site development, and testing for 6 weeks with a small private beta. The plan was to use ‘agile’ principles of web development – launching when the site was not ‘finished’ to gain an understanding of how users actually interacted with the technology, and saving the majority of the development budget for ‘iterations’ of the software in response to user demand.

The resulting site experience can be described as follows: a user coming across the site was presented with two choices: to join an existing investigation, or start their own. If they started an investigation they would be provided with suggestions for ways of breaking it down into smaller tasks and of building a community around the question being pursued. If they joined an existing investigation they would be presented with those tasks – called ‘challenges’ – that needed completing to take the investigation forward. They could then choose to accept a particular challenge and share the results of their progress underneath.

The concepts of Actor-Network Theory (Paterson and Domingo, 2008) were accounted for in development: this describes how the ‘inventors’ of a technology are not the only actors that shape its use; the technology itself (including its limitations and its relationship with other technologies, and institutional and funding factors), and those who use it would also be vital in what happened from there.

Reserving the majority of the development budget to account for the influence of these ‘actors’ on the development of the technology was a key part of the planning of the site. This proved to be a wise strategy, as user behaviour differed in some respects from the team’s expectations, and development was able to adapt accordingly.

For legal reasons, casual visitors to the site (and search engines) could only see investigation titles (which were pre-moderated) and, later, the Reports and KnowledgeBase sections of the site (which were written by site staff). Challenges and updates (the results of challenges) – which were only post-moderated – could only be seen by registered users of the site.

A person could only become a user of the site if they were invited by another user. There was also a ‘request an invite’ section on the homepage. Non-UK requests were refused for legal reasons but most other requests were granted. At this stage the objective was not to build a huge user base but to develop a strong culture on the site that would then influence its healthy future development. This was a model based on the successful development of the constructive Seesmic video blogging community.

On July 1 HelpMeInvestigate.com went live with no promotion. The day after launch one tweet was published on Twitter, linking to the site. By the end of the week the site was investigating what would come to be one of the biggest stories of the summer in Birmingham – the overspend of £2.2m by the city council on a new website. It would go on to complete further investigations into parking tickets and the use of surveillance powers, as well as much smaller-scale questions such as how a complaint was handled, or why two bus companies were charging different prices on the same route.

In the next part I look at the strengths and limitations of the site’s model of working, and how people used the site in practice.