Analysis of world terror networks from the reduced Google matrix of Wikipedia

Abstract

Abstract. We apply the reduced Google matrix method to analyse interactions between 95 terrorist groups and determine their relationships and influence on 64 world countries. This is done on the basis of the Google matrix of the English Wikipedia (2017) composed of 5 416 537 articles which accumulate a great part of global human knowledge. The reduced Google matrix takes into account the direct and hidden links between a selection of 159 nodes (articles) appearing due to all paths of a random surfer moving over the whole network. As a result we obtain the network structure of terrorist groups and their relations with selected countries. Using the sensitivity of PageRank to a weight variation of specific links we determine the geopolitical sensitivity and influence of specific terrorist groups on world countries. We argue that this approach can find useful application for more extensive and detailed data bases analysis.

World Influence of Infectious Diseases From Wikipedia Network Analysis

“…By definition we have the weight W R = 1 for G R and we obtain weights W pr = 0.91021, W rr = 0.04715, W qr = 0.04264 (with nondiagonal weight W qrnd = 0.02667) respectively for G pr , G rr , G qr (G qrnd ). The weight of G pr is significantly larger than others but this matrix is close to the matrix composed from equal columns where the column is the PageRank vector (see also discussions in [18]- [20]). Due to this reason the components G rr and G qr provide an important information about interactions of nodes.…”

“…We consider the network of articles extracted in May 2017 from the English language edition of Wikipedia. This complex network, available at [26] and already used in previous studies [13], [20]- [22], contains N = 5 416 537 articles (nodes) connected through n l = 122 232 932 hyperlinks. From this data set we extract the n d = 230 articles devoted to infectious diseases (see Tab.…”

“…It is also possible to consider the nondiagonal (or indirect) sensitivity D(d → c, c ) = d ln P(c )/dδ when the variation is done for the link from d to c and the derivative of PageRank probability is computed for another country c . This approach was already used in [20] and [21] showing its efficiency.…”

“…In addition to direct links (causal relations) among the n r proteins obtained from literature, the REGOMAX method allows to find possible indirect interactions between the n r proteins due to the embedding of the subnetwork of these n r proteins into the global complex network of proteins. Also, the efficiency of REGOMAX has been demonstrated for the analyses of world terror networks [20], of geopolitical relations between countries [21], and of influence between world painters [22] from Wikipedia networks.…”

World influence and interactions of universities from Wikipedia networks

“…It is also possible to consider the nondiagonal sensitivity D(u → c, c ) = d ln P (c )/dδ when the variation is done for the link from u to c and the derivative of PageRank probability is computed for another country c . This approach was already used in [28,34] showing its efficiency. GE PS BN FO SR SV SN QA KW UZ DO GL GT JO TN CR YE KP UY AE BY LV CY LB LT SA PR CU MA VE SK MM SY BD IQ EE NP VN RS SG IE CL BG CO TH MY CZ UA TW PT EG FI HU IL KR DK GR ID AR BE AT PH CH NO ZA RO TR MX SE IR IN CA AU CN IT JP RU BR ES NL PL SE MX TR RO ZA NO CH PH AT BE AR ID GR DK KR IL HU FI EG PT TW UA CZ MY TH CO BG CL IE SG RS VN NP EE IQ BD SY MM SK VE MA CU PR SA LT LB CY LV BY AE UY KP YE CR TN JO GT GL DO UZ KW QA SN SV SR FO BN BN FO SR SV SN QA KW UZ DO GL GT JO TN CR YE KP UY AE BY LV CY LB LT SA PR CU MA VE SK MM SY BD IQ EE NP VN RS SG IE CL BG CO TH MY CZ UA TW PT EG FI HU IL KR DK GR ID AR BE AT PH CH NO ZA RO TR MX SE IR IN CA AU CN IT JP RU BR ES NL PL SE MX TR RO ZA NO CH PH AT BE AR ID GR DK KR IL HU FI EG PT TW UA CZ MY TH CO BG CL IE SG RS VN NP EE IQ BD SY MM SK VE MA CU PR SA LT LB CY LV BY AE UY KP YE CR TN JO GT GL DO UZ KW QA SN SV SR FO BN PS The world maps of university influence on countries, expressed by the diagonal sensitivity D(u → c, c) for 4 selected universities, are shown in Fig.…”