BBC Global News recently published a special report on Global Migrants, featuring a clickable guide in which the users can explore the 20 most wanted professions across a selection of 30 countries, including those of the OECD, BRICS and Singapore. The project, published in English and other 11 languages, is the result of an investigation by BBC Brasil’s journalist Camilla Costa.

This idea was pitched in the context of a training scheme, to give journalists the time and space to develop their data and visual journalism skills, working hand in hand with other editorial, design and development staff from the Online Specials Team. Camilla led the research and production effort, with Designer Nour Saab, Client Side Developer Martyn Rees and Editor Roberto Belo-Rovella.

The investigation about highly skilled migration focuses on the professions most sought after and how the countries surveyed are changing their legislation to facilitate and manage the admission of those professionals.

The visual guide invites the users to select the profession they are more curious about, to find out which countries are seeking those professionals and then more information about the country in question in the context of migration.

The database compiled confirms the ongoing demand for health professionals, especially nurses, and also the increase in the need for engineering and IT professionals all over the world. But it also shows some surprising facts, such as a demand for chefs, psychologists and even technicians such as radiographers.

How We Went About It

We used data about the migration policies of the OECD countries from the International Migration Outlook 2012 and other OECD reports and lists of professions in demand obtained from Migration Departments and Labour Ministries of the 30 countries explored in this graphic.

Market overviews and surveys were also used for some countries, as well as the data compiled in the European Job Mobility Portal (EURES).

The big challenge was to compile all this information in a consistent way, as the definitions of "highly skilled professions" and their categorizations varied country by country. In many cases we had to request specific information and clarifications directly to government offices in the surveyed countries. The footnotes and methodology story offer detailed information on how it's all worked out, and the full dataset compiled about wanted professions per country.

The research and data compilation took about six weeks. The formatting, design and build took the other six weeks, including the creation of a master version in English and the localisation of the content for 11 other languages.

For compiling and formatting the information we used spreadsheets, mainly Google Documents. Middle East Adobe CS kit was used for mocking up ideas and finalising designs. To be more specific, Illustrator was used to chart the migration flows based on the data provided by the journalists, lay out the other bits of content around it and mark it up for the final hand-over to developers.

Photoshop was used for exporting graphics and preparing assets for the developers. The graphs were supplied in SVG format. In terms of build, HTML and CSS was used for the layout and Javascript to load and display the 50 graphs and also for the interactivity.

Looking Back

The Most Wanted Global Migrants clickable guide and its related content were welcome by the audience, with almost one million page views on the first two days after being published on the BBC News website Business index in English. On Twitter, there were more than 1,400 messages recommending it, and the Migration Unit within the United Nations Alliance of Civilizations also promoted the guide.

It is always a challenge to strike the right balance between being fully comprehensive and presenting the facts in a way that is simple, intuitive for the non-academic or specialised user. We know that online users have very little time to spend, and if they are not immediately attracted to what you have to say online, off they go.

Therefore, once we were clear about what data was actually available to use, and we decided on the story we wanted to tell, they key was to stay focused on that story, and to put the users at its centre.

Would we do it in a different way if we had a second chance? Possibly yes, maybe simpler, maybe more playful, maybe thinking more about mobile devices and responsive design, maybe doing more on the social sphere beyond being able to share information about professions in a particular country on Facebook and Twitter. A big bag of lessons for the next project, no doubt; those lessons that you can only harvest after giving it a proper go.

More than 300 journalists faced threats in Italy in 2012. This is what emerges from the data journalism work by three Italian journalists and developers, Isacco Chiaf, Andrea Fama and Jacopo Ottaviani, who published a cross-platform project that gives a snapshot of the phenomenon.

An interactive map presents the cases recorded in 2012 across Italy, giving a top-down view of the phenomenon. Threats are clustered on the basis of the type: intimidation (104), legal actions (63), assaults (16), malicious mischief (12 cases).

A batchgeo map traces all the cases of threats that involved 324 journalists in 2012 alone.

A more detailed perspective comes from three individual cases of threat that have been represented through timelines including audio, video and other multimedia contents. Through these timelines it is possible to explore unreleased interviews, original documents underlying the investigations, features from the news and the media, and to share them across the social web.

Two more maps show the density of the phenomenon at the regional level, focusing on the number of cases of threat and of journalists involved. The regions recording the most threats are southern Sicily and Calabria.

The density maps show the number of threats recorded in the regions of Italy out of the number of journalists working in them. The southern regions such as Calabria and Sicily show a major presence of the phenomenon.

The project is based on the data by the observatory Ossigeno per l’Informazione ("oxygen for information") which has been monitoring the phenomenon of Italian journalists under threat for years now. In its annual reports Ossigeno sheds light on the situation, recording single stories of threats and aggregating the whole dataset.

How the project was born

The project was born during the DiGiT conference on New Media in Florence, Italy, in July 2013, from an idea of one of the journalists behind the project, Andrea Fama. Andrea talked about the idea of building a new narrative representation of Ossigeno’s data on threatened journalists, by building a set of maps and timelines. In six months we got in touch with the observatory and built up the whole project, with the support of ahref foundation, who financed our work with a grant.

The team consisted of three people coming from three different backgrounds: a data journalist/computer scientist, an artist/designer and a journalist/editor. The three of us share the passion of storytelling and civic journalism. A rational division of work drove the collaboration. However, everyone could contribute to the other colleagues' tasks. 

Advice for journalists

Our suggestion for people who would like to develop similar projects is to specialise in a particular field without forgetting to learn a bit about other fields as well. It helps for programmers to learn how to write news and for journalists to learn how to code. By blurring the boundaries between different skills and backgrounds innovation in the media will be possible. Computer scientists, journalists, statisticians, designers and illustrators should learn to work together and influence each other. Data journalism builds on this blend of skills and experiences.

GiornalistiMinacciati.it is available both in Italian and English. Below is the infographic that summarizes the results.

Figure 1: Type of migration per country in percentages

The pilot project, which analysed and compared the content and tone of press articles about migration published in Canada, France, Germany, The Netherlands, and the U.S. around election periods, indicated that the focus of media coverage is heavily influenced by the societal problems specific to each country. The media in France, for instance, tended to concentrate on the strain migrants allegedly put on the social system, while in the U.S., the press largely reflected on the voting power of migrant groups.

Figure 2: Migration type and topic co-occurrence

An analysis of the co-occurrence of migration types and migration-related topics in the press also indicated the media tend to correlate irregular migrants with law and policy topics, and minorities with issues of citizenship and political participation. These two clusters, in turn, are strongly connected with themes of culture and religion, indicating a trans-national preoccupation with questions of security, identity, and new, ethnic epicentres of political power.

Finally, a study of the articles’ tone revealed an attempt on the media’s part to maintain a neutral perspective towards migrants, an attempt that was at times offset by a tendency to cite one-sided studies or offensive political declarations, without putting them in perspective or counter-balancing them with other sources.

About the pilot study

For this study, the EJC partnered with the University of King's College (Canada), Institut National de l'Audiovisuel (France), Deutsche Welle Akademie (Germany), Christelijke Hogeschool Ede (The Netherlands), and the University of Missouri (United States). The research team took snapshots of press reports on the subject of migration, analysed and coded them according to the related migration topic discussed and the overall tone of the report. All in all, 650 written press articles were collected in the five countries within a four-week time frame surrounding national and regional election periods.

The findings of the study were presented at the 2013 UNAOC Global Forum in Vienna, on 28 February 2013. You can watch a video recording of the panel discussion here.

Yesterday Expert-Grup, an independent think tank based in Chișinău, Moldova, launched BudgetStories.md. BudgetStories.md is an open budget website, which includes infographics, budget data visualizations and analysis of the use of public money in Moldova across sectors such as: the public administration, agriculture, education and health. In recent years Moldovan government has become more transparent regarding budget data as well as other types of data. The Ministry of Finance used the World Bank’s BOOST tool, to release detailed and disaggregated data on public expenditures.

Since mid 2012, we’ve however worked to make sense and meaning in the huge sets of data. In November 2012, while finalizing the project concept, members of the organising team took part in the Balkan Budget Workshop organised by the OpenSpending team. We decided to use OpenSpending as a tool for visualizing Moldova's 2013 budget.

Until now civil society (NGOs, journalists and universities) has shown little knowledge or interest in the existence of open data. Our target groups are mainly journalists and policy makers, who will now with this site for the first time have access to “cleaned data sets”. We are therefore hoping that they will republish and reuse the analysis and visualizations, which could trigger increased public attention to inefficiencies identified in government spending. Also, we’d like to expand the network of stakeholders who use the budget data and disseminate information about how the Government of Moldova spends public money.

It is our hope that this project will create a better understanding among citizens and active members of the society about the way the public finance system operates and the way it influences their everyday lives. If we could reach such increased understanding this could ultimately lead to greater contributions from society to the budget process and more efficient spending of public money.

In the future we plan to add interactive modules such as a real time budget calendar and a tax calculator. You can find out more information about BudgetStories.md on Facebook and Twitter. BudgetStories.md is supported by Soros Foundation Moldova and Open Society Foundations.

While preparing for the real-time challenge of Election night, the WNYC Data News Team -- and the entire city -- turned its attention to an oncoming storm.

For our Hurricane Sandy coverage, we quickly built and maintained several data projects to help convey information people needed. All used open, public data and several were updated regularly -- either automatically or by hand.

Our projects included:

• The evacuation map above, built using public shapefiles from New York City's Department of Emergency Management.
• A storm-surge map for the entire New Jersey and New York coastlines, stitched together from a variety of U.S. Army Corps of Engineers shapefiles.
• A Hurricane Tracker to watch the storm's forecast track and its radar echo, fed by four real-time feeds from the National Weather Service.
• A Transit Tracker with the latest information about several public transportaiton systems, driven by a Google spreadsheet updated by a half-dozen producers and reporters from transportation agency tweets, websites and public announcements.
• A live flood-gauge map showing where the water was rising, driven by a real-time feed from the National Weather Service.
• A traffic map for the back-to-work crush sans subways, fed live by the Google Maps traffic layer.
• A subway-restoration map, updated several times a day with new maps issued by the city transit agency.

For details on the data, follow the source links on each project.

With more time, we would have worked more on the aethetics. But time wasn't something we had much of, so we did our best to be accurate and clear given the resources available.

Read more about the WNYC Data News team's thinking behind our Sandy coverage.

In late 2009, journalist Paolo Gerbaudo was working on an investigative piece when he noticed clear patterns in sinking incidents involving ships suspected of carrying hazardous waste, including radioactive material. Not satisfied with just writing about these ‘accidents’, Gerbaudo contacted MIT researcher David Boardman, an expert in data mapping, and, working together from different continents, got the project off the ground a month and a half later.

“We decided to use information visualisation because the linear format of both written journalism and video journalism were, in our opinion, not effective in conveying the scale of the phenomenon.”

Il fondo al mar - map

Over the last 30 years dozens of commercial vessels have sunk in mysterious circumstances across the Mediterranean, from Spain to Syria, and particularly around Southern Italy. Many suspect the involvement of organised crime syndicates, shady entrepreneurs and even governments in the incidents, generating huge profits in the process. To map these incidents Gerbaudo and Boardman mined the archives of the Lloyds Register of Shipping in London and collected information from press clippings, specialist websites and reports compiled by environmental organisations.

“Looking at that archive, and speaking with people working at the register it seemed very clear that there was something deeply wrong in the frequency with which ships sank around the coasts of Italy in the 80s and 90s.”

The Rosso, an Italian container ship that ran suspiciously aground in 1990. Image courtesy of Legambiente.

Once launched, Il fondo al mar became a participatory project with a strong emphasis on crowdsourcing. Gerbado and Boardman say they have received “tens of emails informing us about other incidents or giving us more information about the ones we had already included in the map,” even corrections to errors in the data. This highlights not only the public interest in the project, but also the level of expert attention it receives. Il fondo al mar also garnered interested among environmental and humanities groups, appearing at international conferences such as MIT’s Digital + Humanities Conference, Ars Electronica and the International Journalism Festival.

Two weeks ago, we published a map showing total NYPD (New York City Police Department) stop and frisks by block together with locations where guns were discovered during such stops. In the tradition of showing our work, here's some information about how we built it -- and data you can download and explore yourself.

The Data

The major bumps I hit working with the NYPD's Stop, Question and Frisk data sets were 1) they're in a format I don't know, and 2) the geographic locations aren't in latitudes and longitudes.

For bump #1, I used the free statistical program "R" to convert the NYPD's ".por" files into something I could use. R is also great at handling big data sets, and easily managed the 685,724 stops in the 2011 file.

For bump #2, I noticed that each stop had data fields called "XCOORD" and "YCOORD." A couple of tests confirmed that those values described the stop's position on the New York-Long Island State Plane Coordinate System -- something I've seen in a lot of city data. So I used the free geographic software QGIS to load in the data and convert (technically, reproject) those coordinates into latitudes and longitudes.

And now you can have the data I used to make the map. Just click to download:

• stopfrisk2011_databundle_sans_allstops.zip

(4.3MB download, unzips to 12MB)
Contains a shapefile of all NYC blocks with the total stop-and-frisks calculated for each block, a shapefile with the points for all stops where guns were found, raw data on each of the 768 stops where guns were found and notes about each data set. Here's more detail on the contents.

• stopfrisk2011_databundle_with_allstops.zip

(51MB download, unzips to 500MB)
This file has of the above and a .csv with the raw data for all 685,724 stops in 2011. While it's in a more common format than what the NYPD provides, it's too big to open in Excel and maxes out the limits for Google Fusion Tables. So you'll need a stats program like R or some database know-how to handle it.

The Map

I built the map using TileMill from Mapbox, which I've been playing with for some months now.

While it's tricker than generating quick maps from Fusion Tables, if you're patient and spend some time with it, you can make some pretty gorgeous maps.

Besides providing wonderful control over styles and colors, TileMill solves an important problem: New York City has roughly 38,500 census blocks -- and loading the data to draw them all onto a Google map will anger any browser. With TileMill, you bake the data into individual image tiles, which get served up to the user as they zoom and pan.

To cover the area of NYC and provide 8 levels of zoom, I pre-cooked 59,095 tiles. But once they're uploaded to the MapBox server, which took about 15 minutes, they load almost instantly.

As always, I welcome comments and questions below or at john (at) johnkeefe.net.

So we’re covering the Eurozone meltdown. Every bit of it. The drama as governments clash and life savings are lost; the reaction from world leaders, austerity measures, and protests against austerity measures. Every day in the Wall Street Journal, there are charts on jobs loss, declining GDP, plunging world markets. It is incremental. It is numbing. 

The Page One editors call a meeting to discuss ideas for year-end coverage and as we leave the meeting, I find myself wondering: what must it be like to be living through this?

Is this like 2008 when I was laid off and dark news was incessant? We talked about jobs and work and money every night at dinner, nearly forgetting how it might upset my daughter. And weekends, they were the worst. I tried to deny the fear that seemed to have a permanent grip at the back of my neck and the anxiety tightening my rib cage. Is this what was it like right now to be a family in Greece? In Spain?

I turned back and followed Mike Allen, the Page One editor, into his office and pitched the idea of telling the crisis through families in the Eurozone by looking first at the data, finding demographic profiles to understand what made up a family and then surfacing that along with pictures and interviews‚ audio of the generations. We’d use beautiful portraiture, the voices—and the data. 

Back at my desk, I wrote a précis and drew a logo.

The Eurozone Meltdown: precis (Wall Street Journal)

For the next three weeks I chased numbers: metrics on marriage, mortality, family size, and health spending. I read up on living arrangements and divorce rates, looked at surveys on well-being and savings rates. I browsed national statistics divisions, called the UN population bureau, the IMF, Eurostat, and the OECD until I found an economist who had spent his career tracking families. He led me to a scholar on family composition. She pointed me to white papers on my topic.

With my editor, Sam Enriquez, we narrowed down the countries. We gathered a team to discuss the visual approach and which reporters could deliver words, audio and story. Matt Craig, the Page One photo editor, set to work finding the shooters. Matt Murray, the Deputy Managing Editor for world coverage, sent a memo to the bureau chiefs requesting help from the reporters. (This was crucial: sign-off from the top).

But first the data. Mornings I’d export data into spreadsheets and make charts to see trends: savings shrinking, pensions disappearing, mothers returning to work, health spending, along with government debt and unemployment. Afternoons I’d look at those data in clusters, putting the countries against each other to find stories. 

I did this for a week before I got lost in the weeds and started to doubt myself. Maybe this was the wrong approach. Maybe it wasn’t about countries, but it was about fathers and mothers, and children and grandparents. The data grew. And shrank. Sometimes I spent hours gathering information only to find out that it told me, well, nothing. That I had dug up the entirely wrong set of numbers. Sometimes the data were just too old.

Judging the usefulness of a dataset can be a very time-consuming task (Sarah Slobin)

And then the data grew again as I realized I still had questions, and I didn’t understand the families. I needed to see it, to shape it. So I made a quick series of graphics in Illustrator, and began to arrange and edit them. As the charts emerged, so did a cohesive picture of the families.

Graphic visualization: making sense of trends and patterns hidden in the datasets (Sarah Slobin)

Numbers are people: the value of data lies in the individual stories they represent (Wall Street Journal)

We launched. I called each reporter. I sent them the charts, the broad pitch and an open invitation to find stories that they felt were meaningful, that would bring the crisis closer to our readers. We needed a small family in Amsterdam, and larger ones in Spain and Italy. We wanted to hear from multiple generations to see how personal history shaped responses. 

From here on in, I would be up early to check my email to be mindful of the time-zone gap. The reporters came back with lovely subjects, summaries, and surprises that I hadn’t anticipated. 

For photography, we knew we wanted portraits of the generations. Matt’s vision was to have his photographers follow each family member through a day in their lives. He chose visual journalists who had covered the world, covered news and even covered  war. Matt wanted each shoot to end at the dinner table. Sam suggested we include the menus.

From here it was a question of waiting to see what story the photos told. Waiting to see what the families said. We designed the look of the interactive. I stole a palette from a Tintin novel, we worked through the interaction. And when it was all together and we had storyboards, we added back in some (not much but some) of the original charts. Just enough to punctuate each story, just enough to harden the themes. The data became a pause in the story, a way to switch gears.

Life in the Euro Zone (Wall Street Journal)

In the end, the data were the people; they were the photographs and the stories. They were what was framing each narrative and driving the tension between the countries. By the time we published, right before the New Year as we were all contemplating what was on the horizon, I knew all the family members by name. I still wonder how they are now. And if this doesn’t seem like a data project, that’s fine by me. Because those moments that are documented in Life in the Eurozone‚ these stories of sitting down for a meal and talking about work and life with your family was something we were able to share with our readers. Understanding the data is what made it possible.

The winning project to be showcased here, Terrorists for the FBI, achieved first place under the category Data-Driven Investigations, National/International category. To see the jury comments click here.

Short video presenting the story behind the Terrorists for the FBI investigation

Conspiracy theories – for real

Mother Jones reporter, Trevor Aaronson found that subsequent to 9/11, the FBI built up a network of 15.000 domestic informants - many of whom were tasked with surveilling and infiltrating Muslim neighborhoods and institutions. As part of this 18-month project, Mother Jones exposed the driving force behind these terrorist conspiracy plots. They discovered that nearly half of the 508 federal terrorism convictions involved the use of informants, many of whom were incentivized by money.

Another major finding was when Nick Baumann, another Mother Jones reporter, uncovered a secret program to have American citizens detained and interrogated by despotic foreign regimes. As a result, the US government confirmed for the first time that domestic law enforcement authorities have a program in place which requests the detention and interrogation of American citizens by overseas regimes.

Uncovering the facts and presenting the story

Terrorism cases state by state

In order to prove that domestic informants do in fact exist, a pattern needed to be established - so a system was set in place. Aaronson spent the next few months researching more than 500 cases in order to build a database that would illustrate exactly how frequently informants were used in terrorism investigations and what role they played. The story began with the case of Gulet Mohamed, a Virginia teenager who, whilst detained in Kuwait, managed to call a New York Times reporter. Mohamed alleged that he was being held and brutally interrogated at the FBI’s behest. The story died down when Mohamed was released, however Baumann didn’t let go. Instead he discovered a series of similar cases, which finally confirmed a pattern.

The investigation heavily relied on federal court records and the database was built from scratch using available court records and information from primary sources. The reporter and a research assistant spent hundreds of hours combing through case files and assembling the database. The team used MySQL and Excel for the first build; as well as Drupal for the online database. 

The investigation also relied on interviews with current and former FBI agents and the use of internal FBI files. In addition, lawyers who defended accused terrorists provided information about their cases. In many cases, the court records were available online. But in other cases, Aaronson had to obtain the records from individual courthouses nationwide or one of the national archive warehouses. Another obstacle was the fact that the federal government does not promote its use of informants. Thus the only way to determine whether an informant was used in a case was to read through the records and find the information buried within.

The unearthed data was presented through charts, graphics, and videos. In an interactive online package, users could search and sort terrorism suspects and check how often they were convicted of lesser charges. Users could also review internal FBI documents, watch surveillance videos, and decode counterterrorism jargon. This project took approximately one year from concept to publication and the core team consisted of five people, plus another dozen team members from the editorial web team.

Screenshot of searchable terror trial database

The challenges

In the competition entry the team behind the project explains: "The FBI is a notoriously secretive organization. As a result it took months of meetings and introductions to put together enough FBI sources to tell the story with authority. The primary challenge was to find the necessary information buried in thousands of pages of court records. Secondly, the information was never in the same place in every court file and thus required weeks of document review. Now the database is available to everyone in searchable form from the Mother Jones’ website."

Advice for aspiring data journalists

"All the information needed is out there; it just needs to be put together. In fact there are many stories like this waiting to written—where a trend can be explained by collecting information no else has assembled. Very few journalists have the time to pursue them today, which makes them all the more critical."

The Data Journalism Awards is a Global Editors Network initiative supported by Google and organized in collaboration with the European Journalism Centre. Please visit the Data Journalism Awards website for the full list of winners.

In March we published a graphic that looks at six variations of a single email sent out by the Obama re-election campaign on the 1st of March.

This all started when fellow news nerd Dan Sinker got an email from the campaign on the same night his wife did and noticed that although they were both apparently from the same person at the campaign — Julianna Smoot — the e-mails had subtle differences. So Dan set up a Google form and asked his Twitter followers to send in their own examples of the “Smoot Email.”

At ProPublica, we’d been wanting to dig more deeply into how “big campaign data” works so we struck a deal with Dan: He’d share his database with us and we’d help analyze and visualize it.

Of course, it was far from a valid sample, but we thought analyzing the data would yield interesting observations if not statistically significant conclusions.

Preprocessing

We found six “clusters” in the 190 emails by grouping the emails using a statistical formula called the Pearson Correlation. More on that in a second.

In order to combat changes in whitespace or accidental insertions or deletions in the emails from influencing comparisons, we used a process called “stemming” to reduce each word to a common prefix. For example the stemmer we used changes the word “writing” into “write” and “journalism” into “journal”. Then we removed common words like “and”, “or”, and “but” from each email.

Finally, we translated each document into a list of word frequencies, which converted each email into an abstract representation called a “bag of words” — like this:

  "curious" => 1.0,
  "elig" => 1.0,
  "told" => 1.0,
  "payment" => 3.0

Stemming, Bagging and Correlating

By treating each email as a “bag of words”, we were able to use the Pearson Correlation to group them together with others in the set.

In statistics, the Pearson Correlation describes the strength of the dependence between two variables. In other words, it is a measure of how two variables change with one another. It returns a value from -1 to 1, with 0 meaning no correlation and 1 meaning perfect positive correlation and -1 meaning perfect inverse correlation. The Pearson Correlation wikipedia page explains the math behind the formula.

To determine whether a document belonged to a group or not, we set the threshold at 0.85.

After running the stemming, bagging and correlating we found that our sample contained six distinct emails.

Diffing and Visualizing

As it turns out the problem of computing differences between documents is very well understood, although it’s quite complex. Rather than implementing our own version of the algorithm, we used one written by John Resig, the creator of jQuery.

Because the emails ranged from very similar to quite different, we wanted an interface that made the variability easy to see at a glance. In addition to a small graphical indicator in the tabs that lets a reader know how strongly other emails match the one inside the tab, a reader can hover over each tab and compare emails very quickly.

In order to keep track of everything client-side, we modeled the data as an array of arrays. We wrote a small table-based javascript framework to do so, which turned out surprisingly like our Ruby-based library table-fu. You can check out the source over on github.

That JavaScript code — we’re calling it table.js — is really easy to use. You can call the regular functional programming methods — each, map, reduce — on each table. It also has simple statistics built in. For example:

Table.js also allowed us to build out the sidebar which shows a simple breakdown of the recipients of each email. Because HTML is really good at displaying rectangles, the graphs in the sidebar are built entirely out of carefully positioned divs.

Correction: This post originally stated that a Pearson Correlation score of -1 meant no correlation, in fact a score of 0 means no correlation, and a score of -1 means negative correlation. The post has been updated to reflect this fact.