The Rise and Fall of Traditional Journalism, Part 4

Part 1 of this series sketches the history of journalism in the U.S. from the pre-Revolutionary era to the present day.Part 2 recalls the emergence of the Internet and the growth of the long tail of online advertising. Part 3 delves into the rise of social media.

Ask someone about the future of journalism, and it’s likely that most people will point to something like E-Ink or perhaps the Amazon Kindle — high-fidelity readers that use millions of embedded, magnetically sensitive spheres which can show a black, white or in-between state to create dynamically refreshing text content. Such readers no doubt have a great deal of potential (along with a number of other display technologies), but while it’s entirely possible that future newspapers will be displayed on such readers, they will also be displayed on laptops and netbooks, on cellphones, on car heads-up displays, the refrigerator, specialized glasses, and ultimately even our shirt-sleeves.

This highlights the real future of journalism — it is increasingly ubiquitous, increasingly participatory, and increasingly germane. Ubiquity is a function of search; participatory is a function of social media; while increasingly germane has to do with a relatively new concept that’s been of largely academic interest in the last few years, but is increasingly entering into common usage — the semantic Web.

What Is Community?

Semantics is one of the more obscure (and philosophical) branches of linguistics, and in the acaddemic sense, semantics is largely preoccupied with the concepts of meaningfulness and relevancy. As such, it tends to be seen as too technical or abstract to be of use to most people. However, in point of fact, semantics (and especially computational semantics) is going to become increasingly central to the way that people work with information systems of all sorts, and most especially news.

One of the most profound changes that the Internet has introduced is the idea that we are transitioning from communities of place to communities of interest. A community of place is geographical — your house, your neighborhood, your city, your region, your state or province, your country, your continent, your hemisphere, your world. For most of recorded history, the degree of relevance of any given thing was inversely proportional to the distance away that thing was. Not surprisingly, your allegiances likewise followed the same relationship. The king may have had more overall power, but in most cases the local lord had far more power over you, and in a struggle between your lord and your king, there was seldom any question of where your true loyalty lay.

Newspapers are very much artifacts of this idea of community of place. A paper is typically associated with a city, or in many cases, with a specific community within that city. A newspaper’s National section may contain news about the country, but in most cases even that news is cherry picked for those pieces of information that may affect the newspaper’s region. The Sports, Business and Lifestyle sections focused on the most proximate sports teams, the doings of the businesses that had a presence in the region, and human interest stories that dealt primarily with the local culture or environment. There are a few exceptions (USA Today comes to mind) but even here its notable that most of their content is still segmented by geography — the USA Today that you pick up in Seattle will have very different news beyond the front page content than the same issue in Atlanta.

In communities of interest, on the other hand, the basis for the community is a particular theme, topic or cause — such as the community surrounding a given computer language, sports team or political ideology. Such communities of interest have, of course, been around for some time, but the difficulty in coordinating communication between members of a given community has typically kept the size of such organizations small and its influence limited. With the rise of the Internet, this is changing.

Shaping Yourself

An interesting case in point is an organization such as Major League Baseball’s Seattle Mariners. As the name would imply, the Mariners are located in Seattle, and as such its fan base tends to be drawn largely from the Puget Sound — with one notable exception. Because the team features two very popular Japanese ball players (Ichiro Suzuki and Kenji Johjima) and the first Asian American coach (Don Wakamatsu), the Mariners have a large and vibrant fan base in Japan, despite appearing only once a year for exhibition games. This latter community is one of interest.

The Web has accelerated a shift that has been underway for a while: As it has become easier for people to communicate with one another across different social media, it has also made it easier for people to find others who have similar interests, coordinate activities, share information, and often to buy and sell within interest-based markets, regardless of where on Earth these people may actually live.

Most social media sites are built around the concept of community interest. Facebook, MySpace, LinkedIn and countless others provide a centralized place for a person to project a particular representation of themselves (an avatar) to the rest of the world, while at the same time acting as windows into interest groups of one form or another. Over time, the more a person becomes involved in a particular media space, the more they invest of themselves in that space, and the more that they shape their particular information sphere.

This filtering process was formerly one of the functions that a news editor performed, determining which particular content would be passed to the readers or viewers within that particular community. The editor as generalist is disappearing; instead, they are being replaced by moderators who act primarily to insure that the inbound content from contributors does not stray too radically from the role of the interest group.

It can be argued that even that function is disappearing, as users of many media services are increasingly able to enable or disable particular channels or news providers. This is the filtering mechanism that is core to Twitter, for instance. You can choose to follow people who other people in your interest circle recommend, and you can also choose to “unfollow” people who provide comparatively little value of interest to you personally. The effect of this over time is the development of a filter “envelope” that provides references to content that is most interesting to you, with comparatively little noise (i.e., the signal-to-noise ratio goes up dramatically). While this may have been an unintended side effect of the original architecture, it is surprisingly effectively.

Put another way, such services let you create your own “newspaper” incrementally, without necessarily choosing to explicitly choose given interest groups or categorizations. This process of increasingly transparent categorization is one of the hallmarks of the current age of journalism; the categorization becomes a function of the likes and dislikes of the reader rather than the editor. Add into this the fact that the reader also is able to effectively “vote” on their favorite news provider (where this information is increasingly at the level of a given writer rather than of an entire news organization), and what emerges is a powerful medium for shaping the news in ways appropriate to the user.

Wearing Blinders?

One argument that’s been raised about this particular filtering and categorization mechanism is that over time, it tends to lock a person into a narrow view of the world, one where alternate ideas are not presented as often and majority viewpoints become self-reinforcing. There’s some validity in that criticism, though it can also be argued that having a human editor in the question provides no guarantee that the content involved will be any more free of bias toward a particular mindset or viewpoint.

Yet consider the counterpoint to this: As such self-filtering becomes the norm, the reader needs to take on more responsibility in seeking out alternate viewpoints. Indeed, this raises the concept of the “responsible information consumer,” in which the information profiles that a person sets up (either directly or indirectly) reflect a more thoughtful approach to understanding the world.

The amount of information on the Internet is reaching a point of inconceivability — the information space is growing faster than any one person, even a voracious reader of this information, could ever take in. It is this fact as much as any that is causing the profession of journalism to collapse — once you remove the requirement that only “formally recognized” journalists can produce content and only “formally recognized” editors can determine what constitutes news, then the amount of content can grow without limit. Through social media tools like Twitter, through blogs, through other similar media, the editorial function becomes a preferential one — “this link is interesting to me … if you have a similar profile to mine, you will likely find the content at the other end of this link interesting too.”

Enter Semantics

Most of these filters act at the document level, but current developments in Semantic Web technology are likely to start performing a fair amount of the analysis at the sub-document level. Document enrichment, encoding terms, people, events, places and things within documents through the use of specialized markup, makes it possible to analyze a document and determine what it’s “about” even if the document doesn’t necessarily use specific terms in that topic.

At a minimum, such semantic analysis makes it easier to create compelling abstracts of articles without human intervention — a remarkably difficult task for humans to accomplish, let alone computers. Yet in conjunction with specific Semantic Web technologies such as RDF, RDFa, OWL, Sparql and other sometimes cryptic acronyms, this also makes it possible for systems to read through collections of blogs, articles and other Web content and make inferences that may not necessarily be obvious to people.

Such an inference engine opens up both possibilities and raises some disturbing issues. One benefit of such a tool is that it makes it possible to perform better prognostications and forecasts (financial and resource allocation, especially), and be able to better determine when there is questionable activity taking place in business, government or elsewhere. The danger here is in failing to recognize that user-generated content does not necessarily just represent true facts, but also contains opinions, distortions, analyses and biased content.

The Rise and Fall of Traditional Journalism, Part 1