Crowd

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A crowd of people returning from a show of fireworks spills into the street stopping traffic at the intersection of Fulton Street and Gold Street in Lower Manhattan Crowd in street.jpg
A crowd of people returning from a show of fireworks spills into the street stopping traffic at the intersection of Fulton Street and Gold Street in Lower Manhattan
A crowd watches the Battle of the Beach 2 - Far Rockaway Skatepark - September, 2019 People watch the Battle of the Beach 2 - Far Rockaway Skatepark - September - 2019.jpg
A crowd watches the Battle of the Beach 2 – Far Rockaway Skatepark – September, 2019
A crowd leaves the Vienna station on the Washington Metro in 2006. July 4 crowd at Vienna Metro station.jpg
A crowd leaves the Vienna station on the Washington Metro in 2006.

A crowd is as a group of people that have gathered for a common purpose or intent. Examples are a demonstration, a sports event, or a looting (referred to as an acting crowd). A crowd may also simply be made up of many people going about their business in a busy area.

Contents

The term "the crowd" may sometimes refer to the lower orders of people in general.

Terminology

The term "crowd" is sometimes defined in contrast to other group nouns for collections of humans or animals, such as aggregation, audience, group, mass, mob, populous, public, rabble and throng. Opinion researcher Vincent Price compares masses and crowds, saying that "Crowds are defined by their shared emotional experiences, but masses are defined by their interpersonal isolation." [1]

In human sociology, the term "mobbed" simply means "extremely crowded", as in a busy mall or shop. "Mobbing", carries a more negative connotation associated with bullying. In animal behaviour, mobbing is a technique where many individuals of one species "gang up" on a larger individual of another species to drive them away. [ citation needed ] Mobbing behaviour is often seen in birds.

Social aspects

A crowd in front of the Presidential Palace on July 21, 1924, in Helsinki, Finland Pohjoisesplanadi 1 - Helsinki 1924 - - hkm.HKMS000005-km0036ey.jpg
A crowd in front of the Presidential Palace on July 21, 1924, in Helsinki, Finland

Social aspects are concerned with the formation, management and control of crowds, both from the point of view of individuals and groups. Often crowd control is designed to persuade a crowd to align with a particular view (e.g., political rallies), or to contain groups to prevent damage or mob behaviour. Politically organised crowd control is usually conducted by law enforcement but on some occasions military forces are used for particularly large or dangerous crowds.

According to Gustave Le Bon, an individual partaking in a crowd adopts certain characteristics such as a decreased ability to think consciously, a predominance of unconscious motives, succumbing easily to suggestion or contagion of feelings and ideas in a similar direction, and tend towards immediately bringing suggestions to action. [2] In his view, most crowds are impulsive, irritable, incapable of reasoning, lack judgement and are fueled by an exaggeration of sentiments. [2] Crowds typically follow an individual or an individual that supports an idea or belief that they deem superior or credible. Le Bon identified two classes of leaders: those that are energetic and have a strength of will and those whose strength of will is enduring, though the latter is thought to be the most impactful. [2] His ideology suggests that the leader should affirm, repeat the affirmation, and foster contagion within the crowd in order to have lasting effects. [2]

Psychological aspects

Psychological aspects are concerned with the psychology of the crowd as a group and the psychology of those who allow their will and emotions to be informed by the crowd (both discussed more comprehensively under crowd psychology).

Many studies on crowds have given insights on how crowds respond to different situations. One 2009 report highlighted many observable behaviors of crowds, [3] including evidence that crowds are able to make united decisions regarding their direction and speed of movement, even if only a few of its members have the information required to make such decisions. [3] The degree to which informed members can affect the crowd depends on their position within the group, with those in the crowd's core likely to have a greater influence. [3]

Generally, researchers in crowd psychology have focused on the negative aspects of crowds, [4] but not all crowds are volatile or negative in nature. For example, in the beginning of the socialist movement crowds were asked to put on their Sunday dress and march silently down the street. A more-modern example involves the sit-ins during the Civil Rights Movement. Crowds can reflect and challenge the held ideologies of their sociocultural environment. They can also serve integrative social functions, creating temporary communities. [5] [4]

Types of crowd

Anarchist crowd during a protest in Mexico City Antifas.jpg
Anarchist crowd during a protest in Mexico City

There is limited research into the types of crowd and crowd membership and there is no consensus as to the classification of types of crowds. Two recent scholars, Momboisse (1967) [6] and Berlonghi (1995) [7] focused upon purpose of existence to differentiate among crowds. Momboisse developed a system of four types: casual, conventional, expressive, and aggressive. Berlonghi classified crowds as spectator, demonstrator, or escaping, to correlate to the purpose for gathering.

Other sociologists distinguished four types of crowds: casual, conventional, expressive, and acting. [8] [9] Casual crowds consists of people aggregated in the same place informally such as a coffee shop. There are also conventional crowds or those that come together for a regularly scheduled event including a church service and expressive crowds that meet to partake in an emotional time together like a wedding or funeral. Lastly, there are acting crowds that join to achieve a common goal or action, which could involve participating in a protest or riot.

Crowds can be active (mobs) or passive (audiences). Active crowds can be further divided into aggressive, escapist, acquisitive, or expressive mobs. [5] Aggressive mobs, which are common in riots, are often violent and outwardly focused. Examples are football riots and the L.A. Riots of 1992. Escapist mobs are characterized by a large number of people trying to get out of a dangerous situation. Incidents involving crowds are often reported by media as the results of panic. [10] [11] However, the scientific literature has explained how panic is a myth which is used to mislead the attention of the public from the real causes of crowd incidents such as crowd crashes. [12] [13] [14] Acquisitive mobs occur when large numbers of people are fighting for limited resources. An expressive mob is any other large group of people gathering for an active purpose. Civil disobedience, rock concerts, and religious revivals all fall under this category. [5]

Movement dynamics

Studies have shown that human crowds move in ways that resemble fluid, [15] [16] and can be modeled by such methods as particle simulation and statistical physics. [17] [18] Similar observations have been made for car traffic [19] and the movement of ant aggregations. [20] [21]

Crowd analysis

This section is an excerpt from Crowd analysis.[ edit ]
Crowd analysis is the practice of interpreting data on the natural movement of groups or objects. Masses of bodies, particularly humans, are the subjects of these crowd tracking analyses that include how a particular crowd moves and when a movement pattern changes. [22] Researchers use the data to predict future crowd movement, crowd density, and plan responses to potential events such as those that require evacuation routes. [23] Applications of crowd analysis can range from video game crowd simulation to security and surveillance.

See also

Related Research Articles

<span class="mw-page-title-main">Flocking</span> Swarming behaviour of birds when flying or foraging

Flocking is the behavior exhibited when a group of birds, called a flock, are foraging or in flight. Sheep and goats also exhibit flocking behavior.

<span class="mw-page-title-main">Crowd psychology</span> Branch of social psychology

Crowd psychology is a branch of social psychology that deals with the ways in which the psychology of a crowd is different from the psychology of the individual persons who are in the crowd. The field of crowd psychology enquires into the behaviors and thought processes of both the individual members of the crowd and the crowd as a collective social entity. The behavior of a crowd is much influenced by deindividuation, a person's loss of responsibility, and the person's impression of the universality of behavior, both of which conditions increase in magnitude with size of the crowd. Notable theorists in crowd psychology include Gustave Le Bon, Gabriel Tarde, and Sigmund Freud. Many of these theories are today tested or used to simulate crowd behaviors in normal or emergency situations. One of the main focuses in these simulation works is to prevent crowd crushes and stampares.

<span class="mw-page-title-main">Swarm behaviour</span> Collective behaviour of a large number of (usually) self-propelled entities of similar size

Swarm behaviour, or swarming, is a collective behaviour exhibited by entities, particularly animals, of similar size which aggregate together, perhaps milling about the same spot or perhaps moving en masse or migrating in some direction. It is a highly interdisciplinary topic.

The expression collective behavior was first used by Franklin Henry Giddings and employed later by Robert Park and Ernest Burgess, Herbert Blumer, Ralph H. Turner and Lewis Killian, and Neil Smelser to refer to social processes and events which do not reflect existing social structure, but which emerge in a "spontaneous" way. Use of the term has been expanded to include reference to cells, social animals like birds and fish, and insects including ants. Collective behavior takes many forms but generally violates societal norms. Collective behavior can be tremendously destructive, as with riots or mob violence, silly, as with fads, or anywhere in between. Collective behavior is always driven by group dynamics, encouraging people to engage in acts they might consider unthinkable under typical social circumstances.

<span class="mw-page-title-main">Crowd simulation</span> Model of movement

Crowd simulation is the process of simulating the movement of a large number of entities or characters. It is commonly used to create virtual scenes for visual media like films and video games, and is also used in crisis training, architecture and urban planning, and evacuation simulation.

<span class="mw-page-title-main">Dephasing</span> Mechanism recovering classical behavior from a quantum system

In physics, dephasing is a mechanism that recovers classical behaviour from a quantum system. It refers to the ways in which coherence caused by perturbation decays over time, and the system returns to the state before perturbation. It is an important effect in molecular and atomic spectroscopy, and in the condensed matter physics of mesoscopic devices.

Evacuation simulation is a method to determine evacuation times for areas, buildings, or vessels. It is based on the simulation of crowd dynamics and pedestrian motion. The number of evacuation software have been increased dramatically in the last 25 years. A similar trend has been observed in term of the number of scientific papers published on this subject. One of the latest survey indicate the existence of over 70 pedestrian evacuation models. Today there are two conferences dedicated to this subject: "Pedestrian Evacuation Dynamics" and "Human Behavior in Fire".

Extremal optimization (EO) is an optimization heuristic inspired by the Bak–Sneppen model of self-organized criticality from the field of statistical physics. This heuristic was designed initially to address combinatorial optimization problems such as the travelling salesman problem and spin glasses, although the technique has been demonstrated to function in optimization domains.

<span class="mw-page-title-main">PTV Vissim</span>

PTV Vissim is a microscopic multi-modal traffic flow simulation software package developed by PTV Planung Transport Verkehr AG in Karlsruhe, Germany. It was first developed in 1992. The name is derived from "Verkehr In Städten - SIMulationsmodell".

Behavioral contagion is a form of social contagion involving the spread of behavior through a group. It refers to the propensity for a person to copy a certain behavior of others who are either in the vicinity, or whom they have been exposed to. The term was originally used by Gustave Le Bon in his 1895 work The Crowd: A Study of the Popular Mind to explain undesirable aspects of behavior of people in crowds. In the digital age, behavioral contagion is also concerned with the spread of online behavior and information. A variety of behavioral contagion mechanisms were incorporated in models of collective human behavior.

Herd behavior is the behavior of individuals in a group acting collectively without centralized direction. Herd behavior occurs in animals in herds, packs, bird flocks, fish schools and so on, as well as in humans. Voting, demonstrations, riots, general strikes, sporting events, religious gatherings, everyday decision-making, judgement and opinion-forming, are all forms of human-based herd behavior.

<span class="mw-page-title-main">Dirk Brockmann</span> German system biologist (born 1969)

Dirk Brockmann is a German physicist and Professor at the Institute for Biology at Humboldt University of Berlin and the Robert Koch Institute, Berlin. Brockmann is known for his work in complex systems, complex networks, computational epidemiology, human mobility and anomalous diffusion.

Dirk Helbing is Professor of Computational Social Science at the Department of Humanities, Social and Political Sciences and affiliate of the Computer Science Department at ETH Zurich.

<span class="mw-page-title-main">Active matter</span> Matter behavior at system scale

Active matter is matter composed of large numbers of active "agents", each of which consumes energy in order to move or to exert mechanical forces. Such systems are intrinsically out of thermal equilibrium. Unlike thermal systems relaxing towards equilibrium and systems with boundary conditions imposing steady currents, active matter systems break time reversal symmetry because energy is being continually dissipated by the individual constituents. Most examples of active matter are biological in origin and span all the scales of the living, from bacteria and self-organising bio-polymers such as microtubules and actin, to schools of fish and flocks of birds. However, a great deal of current experimental work is devoted to synthetic systems such as artificial self-propelled particles. Active matter is a relatively new material classification in soft matter: the most extensively studied model, the Vicsek model, dates from 1995.

<span class="mw-page-title-main">Social contagion</span> Spontaneous spread of behavior or emotions among a group

Social contagion involves behaviour, emotions, or conditions spreading spontaneously through a group or network. The phenomenon has been discussed by social scientists since the late 19th century, although much work on the subject was based on unclear or even contradictory conceptions of what social contagion is, so exact definitions vary. Some scholars include the unplanned spread of ideas through a population as social contagion, though others prefer to class that as memetics. Generally social contagion is understood to be separate from the collective behaviour which results from a direct attempt to exert social influence.

<span class="mw-page-title-main">Self-propelled particles</span> Type of autonomous agent

Self-propelled particles (SPP), also referred to as self-driven particles, are terms used by physicists to describe autonomous agents, which convert energy from the environment into directed or persistent random walk. Natural systems which have inspired the study and design of these particles include walking, swimming or flying animals. Other biological systems include bacteria, cells, algae and other micro-organisms. Generally, self-propelled particles often refer to artificial systems such as robots or specifically designed particles such as swimming Janus colloids, bimetallic nanorods, nanomotors and walking grains. In the case of directed propulsion, which is driven by a chemical gradient, this is referred to as chemotaxis, observed in biological systems, e.g. bacteria quorum sensing and ant pheromone detection, and in synthetic systems, e.g. enzyme molecule chemotaxis and enzyme powered hard and soft particles.

Symmetry breaking of escaping ants is a herd behavior phenomenon observed when ants are constrained to a cell with two equidistant exits and then sprayed with an insect repellent. The ants tend to crowd one door more while trying to escape, thereby decreasing evacuation efficiency.

Collective motion is defined as the spontaneous emergence of ordered movement in a system consisting of many self-propelled agents. It can be observed in everyday life, for example in flocks of birds, schools of fish, herds of animals and also in crowds and car traffic. It also appears at the microscopic level: in colonies of bacteria, motility assays and artificial self-propelled particles. The scientific community is trying to understand the universality of this phenomenon. In particular it is intensively investigated in statistical physics and in the field of active matter. Experiments on animals, biological and synthesized self-propelled particles, simulations and theories are conducted in parallel to study these phenomena. One of the most famous models that describes such behavior is the Vicsek model introduced by Tamás Vicsek et al. in 1995.

<span class="mw-page-title-main">Random sequential adsorption</span>

Random sequential adsorption (RSA) refers to a process where particles are randomly introduced in a system, and if they do not overlap any previously adsorbed particle, they adsorb and remain fixed for the rest of the process. RSA can be carried out in computer simulation, in a mathematical analysis, or in experiments. It was first studied by one-dimensional models: the attachment of pendant groups in a polymer chain by Paul Flory, and the car-parking problem by Alfréd Rényi. Other early works include those of Benjamin Widom. In two and higher dimensions many systems have been studied by computer simulation, including in 2d, disks, randomly oriented squares and rectangles, aligned squares and rectangles, various other shapes, etc.

<span class="mw-page-title-main">Crowd collapses and crushes</span> Type of disaster that occurs due to overcrowding

Crowd collapses and crowd crushes are catastrophic incidents that can occur when a body of people becomes dangerously overcrowded. When numbers are up to about five people per square meter, the environment may feel cramped but manageable; when numbers reach between eight and ten people per square meter, individuals become pressed against each other and may be swept along against their will by the motion of the crowd. Under these conditions, the crowd may undergo a progressive collapse where the pressure pushes people off their feet, resulting in people being trampled or crushed by the weight of other people falling on top of them. At even higher densities, the pressure on each individual can cause them to be crushed or asphyxiated while still upright.

References

Citations

  1. ↑ Public Opinion, by Carroll J. Glynn, Susan Herbst, Garrett J. O'Keefe, Robert Y. Shapiro [ ISBN missing ][ page needed ]
  2. 1 2 3 4 Le Bon, Gustave (1897). The Crowd: A Study of the Popular Mind. T.F. Unwin.
  3. 1 2 3 Challenger, R., Clegg, C. W., & Robinson, M. A. (2009). Understanding crowd behaviours. Multi-volume report for the UK Government’s Cabinet Office. London: Cabinet Office.
  4. 1 2 Reicher, Stephen (2000). Alan E. Kazdin (ed.). Encyclopedia of psychology . Washington, D.C.: American Psychological Association. pp.  374–377. ISBN   1-55798-650-9.
  5. 1 2 3 Greenberg, M.S. (2010). Corsini Encyclopedia of Psychology.[ ISBN missing ]
  6. ↑ Momboisse, Raymond. Riots, Revolts, and Insurrection. Springfield, Ill. Charles Thomas. 1967. [ ISBN missing ]
  7. ↑ Berlonghi, Alexander E. "Understanding and planning for different spectator crowds". Safety Science. Volume 18, Number 4, February 1995, pp. 239–247
  8. ↑ Blumer, Herbert (1939). Collective Behavior (In Robert E. Park, Ed., An Outline of the Principles of Sociology. ed.). New York: Barnes & Noble. pp. 219–280.
  9. ↑ Turner, Ralph; Killian, Lewis (1993). Collective Behavior (4th ed.). Englewood Cliffs, NJ: Prentice Hall.
  10. ↑ Feliciani, Claudio; Corbetta, Alessandro; Haghani, Milad; Nishinari, Katsuhiro (2024-04-01). "How crowd accidents are reported in the news media: Lexical and sentiment analysis". Safety Science . 172: 106423. arXiv: 2309.14633 . doi:10.1016/j.ssci.2024.106423. ISSN   0925-7535. S2CID   262824786.
  11. ↑ Haghani, Milad; Lovreglio, Ruggiero (2022-12-09). "Data-based tools can prevent crowd crushes". Science. 378 (6624): 1060–1061. Bibcode:2022Sci...378.1060H. doi:10.1126/science.adf5949. ISSN   0036-8075. PMID   36480619. S2CID   254485601.
  12. ↑ Fahy, Rita F.; Proulx, Guylène; Aiman, Lata (August 2012). "Panic or not in fire: Clarifying the misconception". Fire and Materials. 36 (5–6): 328–338. doi:10.1002/fam.1083. ISSN   0308-0501. S2CID   145326665.
  13. ↑ Haghani, Milad; Cristiani, Emiliano; Bode, Nikolai W. F.; Boltes, Maik; Corbetta, Alessandro (2019-08-08). "Panic, Irrationality, and Herding: Three Ambiguous Terms in Crowd Dynamics Research". Journal of Advanced Transportation. 2019: e9267643. doi: 10.1155/2019/9267643 . hdl: 11343/227617 . ISSN   0197-6729.
  14. ↑ Haghani, Milad; Coughlan, Matt; Crabb, Ben; Dierickx, Anton; Feliciani, Claudio; van Gelder, Roderick; Geoerg, Paul; Hocaoglu, Nazli; Laws, Steve; Lovreglio, Ruggiero; Miles, Zoe; Nicolas, Alexandre; O'Toole, William J.; Schaap, Syan; Semmens, Travis (2023-12-01). "A roadmap for the future of crowd safety research and practice: Introducing the Swiss Cheese Model of Crowd Safety and the imperative of a Vision Zero target". Safety Science . 168: 106292. doi:10.1016/j.ssci.2023.106292. ISSN   0925-7535.
  15. ↑ Henderson, L. F. (1974-12-01). "On the fluid mechanics of human crowd motion". Transportation Research. 8 (6): 509–515. doi:10.1016/0041-1647(74)90027-6. ISSN   0041-1647.
  16. ↑ Helbing, Dirk; Molnár, Péter (1995-05-01). "Social force model for pedestrian dynamics". Physical Review E. 51 (5): 4282–4286. arXiv: cond-mat/9805244 . Bibcode:1995PhRvE..51.4282H. doi:10.1103/PhysRevE.51.4282. PMID   9963139. S2CID   5771125.
  17. ↑ Helbing, Dirk; Farkas, Illés; Vicsek, Tamás (2000-09-28). "Simulating dynamical features of escape panic". Nature. 407 (6803): 487–490. arXiv: cond-mat/0009448 . Bibcode:2000Natur.407..487H. doi:10.1038/35035023. ISSN   1476-4687. PMID   11028994. S2CID   310346.
  18. ↑ Castellano, Claudio; Fortunato, Santo; Loreto, Vittorio (2009-05-11). "Statistical physics of social dynamics". Reviews of Modern Physics. 81 (2): 591–646. arXiv: 0710.3256 . Bibcode:2009RvMP...81..591C. doi:10.1103/RevModPhys.81.591. S2CID   118376889.
  19. ↑ Helbing, Dirk (2001-12-07). "Traffic and related self-driven many-particle systems". Reviews of Modern Physics. 73 (4): 1067–1141. arXiv: cond-mat/0012229 . Bibcode:2001RvMP...73.1067H. doi:10.1103/RevModPhys.73.1067. S2CID   119330488.
  20. ↑ Tennenbaum, Michael; Liu, Zhongyang; Hu, David; Fernandez-Nieves, Alberto (2015-10-26). "Mechanics of fire ant aggregations". Nature Materials. 15 (1): 54–59. doi:10.1038/nmat4450. ISSN   1476-4660. PMID   26501413.
  21. ↑ Liu, Zhongyang; Hyatt, John; Mlot, Nathan; Gerov, Michael; Fernandez-Nieves, Alberto; Hu, David (2013-11-01). "Ants cushion applied stress by active rearrangements". APS Division of Fluid Dynamics Meeting Abstracts: R11.004. Bibcode:2013APS..DFDR11004L.
  22. ↑ Gamma, "Data-driven Crowd Simulation and Crowd Tracking", UNC at Chapel Hill, 2015
  23. ↑ Jacques, Julio, "Crowd Analysis Using Computer Vision Techniques", "IEEE Signal Processing Magazine", September 2010

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