Reporting The Middle East: Challenges And Chances

Challenges and Chances

Dan Caspi, Daniel Rubinstein

• Publisher: WSPC
• Year: 2017
• ISBN:
  9789813225381
• Topic: Social Sciences
• Subtopic: Media Studies
• Index: Social Sciences

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Numerous studies address the flow of information between nations and states — especially in the era of globalization — and its contribution to the development of relations across physical borders. By contrast, little attention has been paid to the circumstances under which parties in conflict initiate and build barriers to free flow of information. The conflict in the Middle East may serve as a test bed of controlled disruption of information flow, as covered in Reporting the Middle East: Challenges and Chances. Two parallel types of confrontations appear to take place in the Middle East: the actual physical conflict, and the "war of words," conducted via the media, with each side firing its own verbal missiles. Reporting the Middle East: Challenges and Chances aims to show that the media arena is a key element in understanding the Middle East conflict. Media coverage of Middle Eastern affairs remains critical, if only because of its power in determining sources of information, setting decision makers' agendas, and influencing management of the physical confrontation.

--> Contents:

• Dedication
• List of Contributors
• Introduction — Conflict Mediatization in the Middle East (Dan Caspi and Daniel Rubinstein)
• Another View of the Information Wall in the Israeli-Arab Conflict (Dan Caspi and Daniel Rubinstein)
• A Comparative Study of the Syrian Crisis Coverage in Greek and Spanish Traditional and New Media (Pablo Sapag Muñoz de la Peña and Nikos Panagiotou)
• New Content, New Challenges: UGC Use and Challenges Faced by BBC News Journalists Covering Events in Syria (Lisette Johnston)
• Wartime Changes in News Consumption Patterns among Israeli WhatsApp Users: Operation Protective Edge as a Case Study (Ruth Avidar, Yaron Ariel and Vered Elishar-Malka)
• Operation Cast Lead Viewed through Blogs and the Print Press by the Arab Society in Israel (Hama Abu-Kishk)
• "It's Their Fault There's No Chance of Peace": Key Trends in Israeli Coverage of the Israeli-Palestinian Conflict (Hagar Lahav)
• Competing Trends in the Arab Press in Israel: From Print to the Internet (Mustafa Kabha and Dan Caspi)
• Making an Icon: The Al-Dura Conspiracy (Charles Enderlin)

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--> Readership: Students and academics studying political communications, media and communications; students and academics specialising in Middle Eastern politics. -->
Keywords:Middle East;Mass Communication;Political Communication;Mass Media;Media Institutions;Ethnic Media;Public Opinion and PropagandaReview: Key Features:

• This book offers a close analysis of the circumstances in which barriers to free flow of information is initiated and built in the context of media coverage in the Middle East, something that is missing from the numerous similar studies
• A large area of focus is also on news coverage through developments in the use of new media and social media such as WhatsApp and blogs
• Considering the increasing use of "alternative facts" and "fake news", this book can shed some light on how the media arena is a key player in controlling today's information flow

Chapter 1

Examples of Systems

1.1What is a Complex System?

Have you ever been to a live college sporting event, like the basketball game picture in Figure 1.1? An event attended by thousands of enthusiastic fans? If so, then you experienced the great sensation of a crowd’s thunderous cheer as the home team scores. Many who attend college games, in particular, are quite happy to endure inclement weather, traffic snarls, and high ticket prices to experience the comradery and the thrilling feeling of the roar of thousands of people rising to their feet and screaming at the top of their lungs. Crowd responses generate much excitement in each spectator, which further builds the intensity of the response. Even if you become distracted for a moment at a game, you are likely to find yourself compelled to respond just as excitedly to a play as those cheering around you because of some type of connection each of us feels to the crowd that surrounds us. Thunderous cheer is an emergent property of a complex system of spectators in a stadium that is responding to the action on the field.

We do not normally think of crowds of spectators as systems, complex or otherwise, perhaps because we don’t often think of crowds as having unique properties. After all, these people mostly do not know each other. They each come to the game for their own reasons. Despite an apparent lack of central leadership or any agreed-upon organizational structure among the spectators other than shared decorum, the crowd naturally assembles as a group – a thing with distinct properties arising from the act of many individuals communicating in both subtle and overt ways. These self-organized interconnections enable the crowd to respond in unison to common input stimuli, and that response is an emergent property unique to self-assembled crowds. Crowd responses emerge from self-organized interactions among individuals and are not a distinct property of individuals. Therefore, spectators are indeed a complex system. A complex system is an assembly of interacting components each with variable individual properties that self-organize with little to no central control. When the crowd-system receives input stimuli, it responds in a manner consistent with properties that emerge from its network of interacting fans.

Fig. 1.1 Cheering fans at a University of Illinois basketball game. Photo by Cary Frye/Illinois Athletics, December 2, 2015 (with permission).

Now consider a different complex system – a Midwestern Prairie. It too has properties not wholly due to any one of its components. The components of the Midwestern Prairie complex systems include various types of grasses, plants, animals, insects and micro-organisms. The interactions between these components give rise to the emergent properties of the prairie systems that, among other things, determine how it responds to various climatic conditions such as extended periods of draught or heavy rain fall.

Grasses dominate life in a natural prairie, and they survive because of the support they receive from other plants and animals that live codependently. Each organism responds individually, cooperatively, and antagonistically with respect to others and to the environmental inputs. Prior to European settlement, prairielands in the Midwestern United States may have extended as much as a million square miles (640 million acres). On the eastern side of the Midwestern prairie, including Illinois and Iowa, the prairie appeared to settlers mainly as a “sea of tall grasses,” most 2-3 meters tall, consisting of mixtures including Big Bluestem and switch grasses that were mixed with a wide variety of wildflowers and a few trees. Today, that rich diversity of plants has been replaced by a crop grass – field corn – and its synergistic partner, soybeans. Only small isolated patches of the original prairies remain, although some local governments and citizen organizations are attempting to restore more of it.

Fig. 1.2 (a) A patch of Midwestern Prairie in Illinois. (b) A “graph” of interacting prairie components is illustrated. Gray components are dominant grasses, green components are other plants, the red components are various insects, and blue components are environmental inputs like climate and soil conditions. Lines connecting component nodes, labeled w, indicate the strength of that interaction.

Adjacent states to the west, Nebraska, Kansas, and Oklahoma, which were once dominated by a diverse mixture of medium-length grasses like Little Bluestem and wheat grasses, have now been replaced by mostly wheat crops. States in the western-most region of the prairielands, Montana, Wyoming, and Colorado, once populated by shorter Buffalo-grass varieties are now rangeland for cattle and sheep. The type of grasses that developed in a region depended on climate, soil type, and average moisture content. In each region, plants and animals were self-selected for their ability to live together and thrive despite climates of high wind, intense direct sunlight, and long periods of dry conditions. We might begin to analyze this complex network of components by diagramming the relationships among prairie species and their environmental factors using graphs like that in Figure 1.2. The goal of the analysis is to determine how system properties emerge from component connections.

Human agriculture has reduced the diversity of life provided by prairielands considerably, which concerns environmental scientists. Diversity of species in the environment helps the prairie system ward off the spread of disease brought about by, for example, climate change and the introduction of non-indigenous invasive species. Component diversity and property variability are important features of any natural complex system. In Chapter 6, we describe how diversity and variability in component properties are essential for creating the system and maintaining a consistent “balance” so that system properties are able to emerge and establish a norm – an equilibrium state. Predicting the behavior of complex systems, especially those much more complex than human social behavior during a basketball game or even life in a Midwestern Prairieland, is at the heart of the most difficult problems facing society. For scholars in all fields, managing complex systems is the central intellectual challenge of this century.

Prairies are compelling illustrations of a complex system because they are familiar to those most concerned about the effects that civilization is having on our planetary environment. A prairie consists of and is sustained by its biome, which is a regional community of animals, insects, plants, and microbes that have, over time, both modified and adapted to the local soil, climate and terrain. Species both determine and are determined by the ecosystem they constitute. As stewards of our planet, mankind recognizes its obligation to identifying biome components and understands how they interact to balance competing forces within the ecosystem that sustain life on our planet.

1.2Flock of Birds

The fascinating behaviors of flocking birds, swarming insects, and schooling fish are standard examples of complex adaptive systems. In each case, a countable number of components each follow a few simple individual rules to achieve complex group behavior. The simplicity of individual behavior provides insights into system properties and component interactions through modeling. And yet, this simplicity is the exception rather than a rule. Most complex systems, as we will see later, are too “complex” for us to clearly understand how their internal workings give rise to emergent properties.

Fig. 1.3 Two images of flocking birds. The top image is from Shutterstock. The lower photo is by Anthony Moyes.

Who has not marveled at the amazing aerobatic feats of hundreds, maybe thousands of birds as they seem to flow in lockstep through the air in intricate three-dimensional patterns? (See Figure 1.3). Birds use flocking behavior for many reasons, including protection against predators, efficient identification of food sources, minimizing the energy expended when flying long distances, finding a mate, and raising offspring. Depending on the task at hand and the environment in which the group finds itself, flocking birds execute aerial displays without coordinated leadership. Flocking behavior is a property of the system that emerges from individuals provided they are able to efficiently communicate and they adhere to a few simple rules. Deriving complex group responses from simple individual responses has fascinated scholars from all fields because most of us intuitively feel that this simple example could be a path to discovering fundamental principles governing all complex systems.

First consider a group of birds foraging for food. A good time to observe this behavior is in the summertime just after a large grassy area is mowed. If you casually walk by these birds that are busy eating newly exposed insects, you find a few skittish birds will fly away, prompting others to do the same. Others stay behind and ignore your passing. Of those that fly away, some may fly to treetops beyond your reach until you are gone, while others fly just a short distance and quickly return once you pass by. This variation in individual behavior can help systems remain in equilibrium despite a changing environment and, indeed, changes to the system itself.

Individuals in the group self-organize through visual and auditory signals to achieve synergistic goals, which in this example include locating food while monitoring the threat level. A property that emerges from flocking behavior is easier location of and safer access to food sources than might be expected by individuals venturing out on their own. It is significant that, although each bird has ostensibly the same instinctual rule set for how to react in the foraging situation, individuals freely respond with much variability to the same input. One can imagine that an appropriate degree of variability among the movement of individuals affords the group with greater opportunity for foraging success. Variation in behavior provides other advantages and challenges to the group.

The situation changes entirely when the group task suddenly switches from foraging to aerial evasion of a predatory bird. It is one thing for a group of foraging starlings to be wary of a slow-moving human walking by, and quite another when a hawk attacks them from the air. Once the hawk is detected, each starling narrows its list of possible rules of behavior to just a few so that variance among individuals is reduced. The hawk’s strategy is to isolate an individual from the flock where it can use its size and speed to focus its effort. The starlings react instinctually to spatially vary their number density in the air while being careful to not separate from the group. They do this by continuously splitting and merging subgroups without separating from the flock. In this way they achieve their synergistic goal of confusing the hawk who the starlings hope will tire and disengage. What are the simple rules that enable instantaneous coordination of efforts even when the rules are intuitively understood and variably applied without the aid of central leadership?

This was the question asked by Andrea Cavagna, a condensed-matter physicist living in Rome. He leads StarFlag, a multinational collaboration of scientists dedicated to the study of bird flocking behavior because of what it can teach us about complex systems [Attanasi et al. (2014)]. The group’s initial effort was to image in time the movements of each bird within a large flock. They hoped to understand flock shapes from individual bird movements using probability theory in a manner analogous to the way bulk material properties can be predicted from molecular movements in statistical mechanics. The StarFlag group inferred the rules of individualbird behavior that could be synthesized in a computational model to study and predict responses of the flock to inputs similar to those observed in nature.

Bird movements were measured in three dimensions using stereoscopy. Each frame in a stereoscopic movie consists of a pair of images recorded simultaneously from perpendicular angles. These two views allowed the scientists to track the location and velocity of more than 1000 starlings in a flock under different environmental conditions. They observed that as a hawk approached, the starlings closest to the hawk took straightforward evasive measures. But it was the behaviors of those around the point of attack that generated defensive flocking behavior.

They found that individual birds followed three basic rules: (a) their strongest impulse was to move away from neighbor starlings in closest proximity to avoid collisions (strong short-range repulsion); (b) their weakest impulse was to move toward the bulk of the group to avoid separation (weak long-range attractions); and (c) in between the short and long ranges, starlings moved in patterns most sensitive to the direction of the flight of the nearest 6-7 neighbors, preferring to fly closer to neighbors on either side of them than those in front or behind (intermediate-range alignment). Interestingly, the lateral intermediate-alignment rule correlates with the angular variation in the visual-field sensitivity of a starling. One can debate whether the high sensitivity for seeing birds along each side is a cause or an effect of the intermediate-alignment rule. By following these three simple rules within the physical limitations of perception, cognition, and flight, the flock was able to rapidly vary bird density and thus minimize risk during an attack. These rules are representative of the type used in agent-based models as discussed in Chapter 6.

It is also interesting how differently the flock behaves in the foraging and predator-attack environments. We would say that the onset of a hawk attack triggered a change in flocking behavior, where the same birds are now expressing very different emergent properties because they are behaving as part of a complex system. In the defensive state, individual behavior narrows to focus on three basic rules until the threat passes and the system returns to a more relaxed state. The effects of a tightened rule set combined with perception-reaction delays and flight maneuver times produce the rapidly varying bird density. This defense strategy must be robust against birds leaving and joining the flock. If the hawks adopt pack-hunting strategies, which may negate the primary effects of flocking behaviors, then starlings must also adapt.

The starling’s defense strategy raises an important question: why do predators continue attacking bird systems that have evolved flocking behavior to protect themselves from predators? If the predators are not successful at achieving their goal of preying on members of these systems, it is reasonable to assume that they would eventually realize this and stop attacking these systems to avoid wasting energy. But they continue attacking them. Now we see another role for variability. Flocks of birds and schools of fish have evolved to provide protection from the predators for most, but not all, of their members. Some members become weak, old, or sick and so may not be able to keep up with others over the extended period of time needed to evade attack. They will separate as the flock tries to operate outside the capabilities of these individuals, and hence they are more likely to be lost to the hawk’s attack. By continually attacking the flock, predators cull the weakest individuals and thus become a driving force in the long-term evolution of the starling species.

Bird flocks, fish schools, and insect swarms are relatively simple complex adaptive systems, which is why many authors select them to illustrate their basic features. The ability of a system to adapt to environmental stimuli, by the system slowly changing as a direct result of the stimulus, is a defining feature of life. But nature is filled with much more complicated and interesting systems.

1.3Early History

As academics, we are occasionally asked about emerging ideas and their potential influence on society decades from now. It is thought we might know something about these trends because we spend so much time looking for isomorphisms, which are common features shared by disparate problems. As it will become clear throughout this book, we feel strongly that the development of new methods for studying and analyzing complex systems is among the most important problems of the 21st century, but this is not a new problem.

Beginning in the 1930s, biologist Ludwig von Bertalanffy began formulating the physical principles governing biological-system ontogeny. Ontogeny is the study of how an organism develops from a fertilized egg through adult maturity, and at the time scientists were just beginning to organize details of a field now known as developmental biology. The ideas that emerged from his studies blossomed into what he called the General System Theory that he felt had very broad applications in nature [Bertalanffy (1950, 1951, 1972)]. To explain Bertalanffy’s contributions, we first discuss a few statistical facts about developmental biology and some college-level physics.

It is incredible to think that each of us begins our development from just a single cell (zygote). The large, roughly 0.2-mm-long zygote weighs just 8 micrograms (0.000008 g). It voraciously consumes mass and energy to repeatedly divide over 9 months to result in a 3000 g infant composed of about 3 trillion cells (3,000,000,000,000). Not only do these cells quickly multiply, most cells precisely specialize their form and function, i.e., differentiate. Cells also move among other cells and orient their positions relative to an accumulation of like cells to form organs, limbs, and all anatomical features we recognize as human. After birth, the nascent body continues its growth and development, such that in two decades the 80 kg adult human will consist of roughly 80 trillion cells plus an additional 800 trillion bacteria, fungi, and archaea of more than 500 different types. These other organisms are so small that they add only about 2 liters t...

Table of contents

• Cover Page
• Title
• Copyright
• Dedication
• Preface
• Contents
• Preface
• 1. Examples of Systems
• 2. System Properties
• 3. Knowledge Discovery
• 4. Examples of Mechanical Systems Undergoing Transitions
• 5. Biological Systems
• 6. Role of Variability in Systems
• 7. Epilogue
• Bibliography
• Index