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Investigative Data Mining: Mathematical Models for Analyzing, Visualizing and Destabilizing Terrorist Networks

von Nasrullah Memon

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[1.] Nm/Fragment 085 01 - Diskussion
Zuletzt bearbeitet: 2012-05-11 22:14:39 WiseWoman
Berry etal 2004, Fragment, Gesichtet, Nm, SMWFragment, Schutzlevel sysop, Verschleierung

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Seite: 85, Zeilen: 1-7
Quelle: Berry_etal_2004
Seite(n): 2, Zeilen: left column: 15-20
He further states that they have formed into social networks or “clusters” based on some common experience. Their commonality is based on their expatriate status which results in a level of isolation. Their status in the host country and their shared assumed sense of isolation result in the development of clusters. Berry N. et al integrated agent based and social modeling approach in the Seldon project. Second, they have formed into social networks or ‘clusters’ based on some common experience. Their commonality is based on their expatriate status which results in a level of isolation. Their status in their host country and their shared assumed sense of isolation result in the development of clusters. [...]

This analysis of the basis for participation supports the integrated agent-based and social network modeling approach we have taken with Seldon.

Anmerkungen

The source is only mentioned in the last sentence, the extent of the text taken is not made clear.

Sichter
(Hindemith), WiseWoman

[2.] Nm/Fragment 085 08 - Diskussion
Zuletzt bearbeitet: 2012-05-11 21:55:19 WiseWoman
Clauset Young 2005, Fragment, Gesichtet, Nm, SMWFragment, Schutzlevel sysop, Verschleierung

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Seite(n): 5, Zeilen: 5: 1st column, 36ff;
In exploring the distribution of the severity of events in global terrorism, Clauset Aaron and Maxwell Young (2005) found a surprising and robust feature: scale invariance. Traditional analyses of terrorism have typically viewed catastrophic events such as the 1995 truck bombing of the American embassy in Nairobi, Kenya, which killed or injured more than 5200. However, the property of scale invariance suggests that these are instead a part of a statistically significant global pattern in terrorism. Further, they showed that there is little reason to believe that the appearance of power laws in the distribution of the severity of an event is the result of either reporting bias or changes in database management.

There are many generative mechanisms in the literature for power laws, although many of them are unappealing for explaining the structure (Maxwell Young, 2005) found in global terrorism. The highly abstract model of competition between non-state actors and states, which they proposed, analyzed and extended via the mixtures model, is likely to be too simple to capture the fine structure of global terrorism. However, their model and the statistically significant empirical regularities which showed by the author will frame future efforts to understand global terrorism.

In exploring the distribution of the severity of events in global terrorism, we have found a surprising and robust feature: scale invariance. Traditional analyses of terrorism have typically viewed catastrophic events such as the 1995 truck bombing of the American embassy in Nairobi, Kenya, which killed or injured more than 5 200, as outliers. However, the property of scale invariance suggests that these are instead a part of a statistically significant global pattern in terrorism. Further, we find little reason to believe that the appearance of power laws in the distribution of the severity of an event is the result of either reporting bias or changes in database management. [...]

[2nd column, 31ff]

There are many generative mechanisms in the literature for power laws, although many of them are unappealing for explaining the structure we find in global terrorism. The highly abstract model of competition between non-state actors and states, which we propose, analyze and extend via the mixtures model, is likely too simple to capture the fine structure of global terrorism. However, we hope that our model and the statistically significant empirical regularities which we show here will frame future efforts to understand global terrorism.

Anmerkungen

In describing the findings of Clauset & Young (2005), Nm actually copies quite literally from their paper, which is not mentioned in the bibliography. Note that reference is also made to "Maxwell Young, 2005", which, however, is probably meant to be the same paper. The name of the first author is Aaron Clauset, not Clauset Aaron.

One could also classify this as a pawn sacrifice ("Bauernopfer"), since a partial reference is given, although the extent of the text taken is not make clear.

Sichter
(Hindemith), WiseWoman

[3.] Nm/Fragment 085 28 - Diskussion
Zuletzt bearbeitet: 2012-04-20 22:09:37 WiseWoman
Fragment, Gesichtet, Nm, SMWFragment, Schutzlevel sysop, Verschleierung, Xu etal 2004

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2.13.2 Statistical Methods

Statistical analysis examines social network dynamics quantitatively. It aims not only to identify and examine the network changes, but also to account for the causes which brought these changes. Structural changes are assumed to result from some [stochastic processes of network effects such as reciprocity, transitivity, and balance (Snijders, T.A.B., 2001).]

3.1.2 Statistical Methods

Statistical analysis of social network dynamics aims not only at detecting and describing network changes but also at explaining why these changes occur. With statistical methods, structural changes are assumed to result from some stochastic processes of network effects such as reciprocity, transitivity, and balance [EN 34].


[EN 34]. Snijders, T.A.B. (2001). The statistical evaluation of social network dynamics. Sociological Methodology, 31, 361-395.

Anmerkungen

No source given. Text continues on the next page: Nm/Fragment_086_01

Sichter
(Hindemith), WiseWoman


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