30 Matching Annotations
1. Feb 2018
2. www.scienceintheclassroom.org www.scienceintheclassroom.org
1. P. Manrique et al., Context matters: Improving the uses of big data for forecasting civil unrest: Emerging phenomena and big data. IEEE Intelligence and Security Informatics (IEEE, 2013), pp. 169–172. J. Matheny, Test and evaluation in ACE and OSI IARPA (2013); available online at http://semanticommunity.info/@api/deki/ files/21696/3-ACE_and_OSI_NIST_Brief.pdf.

Several co-authors of this paper participated in a recent IARPA project to help build a reliable database of civil unrest events across countries in Latin America.

2. Second, if anti-ISIS agencies are insufficiently active in countermeasures and hence the overall rate at which they fragment pro-ISIS clusters becomes too small—specifically, if the aggregate fragmentation rate vfrag < (NlnN)–1—then pro-ISIS support will grow exponentially fast into one super-aggregate (fig. S11).

The rationale here is that if anti-ISIS agencies do not shut down smaller aggregates at a sufficient rate, these aggregates will merge (coalesce) into bigger ones, which will be harder to shut down. Eventually, this process will repeat until a "super-aggregate" is formed, which will be very hard to shut down.

3. robust

In statistics, the term robust or robustness refers to the strength of a statistical model, indicating that the model has good performance for data drawn from a wide range of probability distributions.

4. power-law distribution

A power law is a functional relationship between two quantities, where one quantity varies as a power of the other.

An example of a power law is Zipf's Law, which says that the distribution of words in a given corpus of text is a function of the frequency of the words. In a given corpus of text, the most frequent word occurs twice as much as the second most frequent one, which shows up twice as much as the third most frequent one, and so on.

5. stochastic

A stochastic event has a random probability distribution or pattern that may be analyzed statistically but may not be predicted precisely.

An aggregate shutdown is a stochastic event because it depends on the probability of that aggregate being found by predators (entities capable of shutting it down).

6. fragmentation

An aggregate is fragmented when it is broken down into other aggregates of smaller size. This happens, for instance, when an aggregate is shut down.

7. We fit the trend in the creation dates of new online aggregates (Fig. 2, A and B) to a well-known organizational development curve (19)

The curve mentioned here is the progress curve analysis of organizational development. Using the formula for this curve, the time interval between the creation of the n-th and (n + 1)-th aggregate is given by:

$$\tau_n = \tau_1 n^{-b}$$

If b is zero in the formula above, then the creation of aggregates would depend only on the previous number of aggregates. However, in the authors' experiments, b is different from zero, which indicates that there is some perturbation (escalations and de-escalations) to the process of aggregates creation.

8. bipartite graphs

A bipartite graph is a set of graph vertices decomposed into two disjoint sets such that no two graph vertices within the same set are connected.

In the paper, the disjoint sets of nodes that constitute the bipartite graph are aggregates and followers. In this graph, there are no direct connections between aggregates (they can only be connected through other people). The same holds for followers: they are connected to aggregates, but not (directly) to other followers.

9. Our methodology for identifying these pro-ISIS aggregates was as follows.

As from the Supplementary Material, the manual analysis described here can be broken down into the following steps:

• Experts search websites such as VK.com for common hashtags and keywords on a daily basis.
• A manual list of aggregates, which was updated daily, was assembled by the experts to include only those aggregates appearing to express a strong allegiance to ISIS.
• To find newly created aggregates, the experts analyze posts and reposts among known aggregates, as well as follow selected profiles that actively publish ISIS news.
• Newly found aggregates were included in the authors' database.
• The database of aggregates was analyzed on a daily basis to determine which aggregates were still active and which were shut down.
10. The data show that operational pro-ISIS and protest narratives develop through self-organized online aggregates, each of which is an ad hoc group of followers of an online page created through Facebook or its global equivalents, such as ВКонтакте (VKontakte) at http://vk.com/

An account page created on Facebook or VKontakte can be marked as an "organization". These pages are often used for informal organizations or groups of people interested in a particular subject. In the case of pro-ISIS aggregates, the pages contain material expressing a strong allegiance to ISIS and are followed by people interested in such material.

In the Supplementary Material, the authors point out that pages containing ISIS-related content are almost imediately shut down on Facebook and that such pages experience longer lifetimes on VKontakte.

11. attack in San Bernardino in December 2015

A terrorist attack consisting of a mass shooting and an attempted bombing at the Inland Regional Center in San Bernardino, California, in which 14 people were killed and 22 others were seriously injured.

Self-radicalization is a phenomenon by which individuals become terrorists without affiliating with a radical group, although they may be influenced by its ideology and message.

13. attacks in Paris in November 2015

A series of coordinated terrorist attacks that occurred on Friday, November 13, 2015, in Paris, France. In the first attack, three suicide bombings occurred outside a football match. The second consisted of several mass shootings and a suicide bombing at several cafés and restaurants. The third was a mass shooting at a concert.

14. aggregates

An ad hoc group of followers of an online page that interact in a language-agnostic way and with freely chosen names that help attract followers without making public the identities of the group's members.

The paper uses the term aggreagates in three ways:

1. as a members of an ad hoc group of followers on an online page (as defined above);
2. as refering to pro-ISIS aggregates, which are aggregates that appear to express a strong allegiance to ISIS;
3. in contrast to followers, which are people who interact with aggregates online.

In the Supplementary Material, the authors provide a link to a video showing how agrregates can be set up for any purpose on Facebook, VKontakte, and other similar websites.

15. ecology

The term "ecology" can be defined as the set of relationships between a complex system and its surroundings or environment. In the context of this paper, the relationship between pro-ISIS ad hoc groups formed online constitutes an ecology. It can also be interpreted as "ecosystem" in this context.

16. iterated

A process that is repeated several times until a desired outcome is reached.

17. Q. Zhao, M. Erdogdu, H. He, A. Rajaraman, J. Leskovec, SEISMIC: A self-exciting point process model for predicting tweet popularity, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Sydney, 10 to 13 August 2015.

The authors propose a way of predicting the final number of reshares of a given post on social networks.

18. D. Koutra, D. Jin, Y. Ning, C. Faloutsos, Perseus: An interactive large-scale graph mining and visualization tool (DEMO), VLDB 2015, Kohala Coast, Hawaii, 31 August to 4 September 2015.

The authors propose a tool, called Perseus, that makes it easy for the user to analyze large graphs by supporting the coupled summarization of graph properties and structures, guiding attention to outliers, and allowing the user to interactively explore normal and anomalous node behaviors.

19. First, anti-ISIS agencies can thwart development of large aggregates that are potentially far more potent (21) by breaking up smaller ones.

This result may seem counter-intuitive, but it makes sense when we consider the costs of shutting down larger aggregates versus the costs of shutting down smaller ones. It is easier to shut down smaller aggregates.

20. goodness-of-fit

The extent to which observed data match the values expected by theory.

In this context, the value P = 0.86 says that 86% of the values observed matched those predicted by the proposed model.

21. coalescence

This process happens when an unattached follower is combined to an aggregate, or when an aggregate is absorbed into another.

22. shark-fin shapes

The shapes resembling parts of a shark's body. These shapes are shown in the chart by an increase followed by an abrupt drop.

23. The escalation parameter b diverges at these real-world onsets (Fig. 2, C and D) and follows the same mathematical dependence (Tc – t)–1 as a wide class of physical phase transitions (20), with the divergence date Tc matching the actual onset almost exactly (SM).

A phase transition is an abrupt, discontinuous change in the properties of a system. It happens, for instance, when a liquid turns into a gas. The equation describing such transition is the one shown here in the paper:

$$(T_c - t)^{-1}$$

In the context of the paper, the authors model the onset of an event as a phase transition using the formula above. They also argue that this formula can be used to predict the future time for an onset of a real-world outburst.

24. following the U.S. Open Source Indicator (OSI) project (14–16)

The goal of (14,15) was to help build a "Gold Standard Report" (GSR) reliable database of civil unrest events across countries in Latin America.

Links that appear within a given post.

26. application programming interfaces

An Application Programming Interface (API) is a set of clearly defined methods of communication between various software components.

27. drone strikes

Drone strikes have been used to combat ISIS fighters.

28. ecosystem

A community of interacting agents and their environment. In the context of this paper, the ecosystem has interacting agents (aggregates and followers), an environment (the Internet), and even predatory entities (police cybergroups, individual hackers, and website moderators).

29. Our data sets consist of detailed second-by-second longitudinal records of online support activity for ISIS from its 2014 development onward and, for comparison, online civil protestors across multiple countries within the past 3 years

On a daily basis, experts looked for specific hashtags and keywords that indicated activities related to ISIS or to civil unrest. Then, at the same time each day, these experts logged into VK.com--an equivalent of Facebook that is popular in Europe--and searched for newly created aggregates, which were then inserted into a database.

30. longitudinal records

Records of the same variables, which in the case of this paper are hashtags that may suggest ISIS-related activity, observed over a given period of time.