جستجوی مقالات مرتبط با کلیدواژه "خوشه‏بندی" در نشریات گروه "ادبیات و زبان ها"

Kinship terms have always been an interesting topic for anthropologists from a social relation and interaction point of view, and for linguists for their structural, typological, and historical aspects. Applying methods of dialectometry (Seguy, 1973), including distance matrix, MDS maps, cluster maps, and dendrograms and using Gabmap (Narbonne et al.,2011) for the computational analysis, this study is aimed at discovering the similarities and differences between 704 tokens of kinship terms(Consanguinity and affinity) in 32 varieties spoken in 5 provinces including Yazd, Hamedan, Kerman, Isfahan, and Farsand measuring their distances and closeness to each other and the Standard Persian. Results revealed that phonological and lexical diversity in borrowed terms from Arabic referring to the son’s wife, mother’s sister, father’s brother, and father’s sister is less than other terms. Based on clustering in 10 groups, there is more diversity among the varieties inside Isfahan province. There is less dialect distance among the varieties inside Kerman province, except for a variety in Jiroft which shows more similarities to Hamedan varieties probably due to Lor and Lak populationin both areas.Varieties in Hamedan are grouped as a cluster too, except for a variety which is closer to the Standard Persian. Therefore, linguistic borders and geographical borders are not the same.The largest group includes 13 varieties of Kerman, Fars, Yazd (near birderlines), and southwest, and west of Isfahan near the borderline with Fars. In fact, near borderlines between these provinces, there is a dialect continuum. Two varieties in Isfahan, one in Yazd and one in Hamedan are the closest varieties to the Standard Persian. Kesheh and Tallabad which are probably related to Raji and Ardestani (dialects of central Plateau) can be considered as language islands.

Translation and publication of the Persian novel in the epic genre after the revolution and war; especially in the West, despite the rapid, growth of quantity, major changes and new forms of content, has been very slow. It seems, Regardless of the political aspects and disagreement of the sacred and ideological content of these works with a Western audience, at least, Failure to discover and selecting suitable examples of existing novels – which have most harmony with Western taste - is something that by Attention and correction, can be Reinforcement for Publication and promotion these works outside Iranchr('39')s borders. In this article, a random selection of war novels based on rhetorical (audience-based) criticism, Based on the national psychology of the English people as exemplified, in the manner of Kenneth Burke, is criticized and analyzed. The critique and analysis of the three novels "Clash" "Under the Cherry Tree" and "In Search of me", which are almost at the top, below and in the middle of this adaptive spectrum, are fully embodied. The result is a wide and varied range of maximum to minimum conformations, as the capacity for acceptance and persuasion by the English audience. So it seems, on the possibility of promoting and propagation a Persian novel in England, we should have to go into detail: some of these works are well-suited to be present in the UKchr('39')s cultural space, and some are not. A group may also, with some form of editing, find the context needed to better communicate and attract Western audiences for persuasion and influence. The results can also serve as a mirror for Iranian writers to expand their global audience.

Mutation in DNA, migration, natural selection, type of non-random matting (such as consanguineous marriages) and genetic drift (in small size populations) are factors caused alterations of allelic frequencies in populations (Saadat and Amirshahi 2011, 1-12). The above-mentioned factors are evolutionary forces. Folktales, like living organisms, have evolutionary pathways. Folktales experience sudden changes (mutation), and moving from a population to another population (migration). Some parts of folktales change according to some environmental factors (such as economic, political and cultural), which is very similar to natural selection. Some parts of different folktales join with each other, which is similar to non-random matting. Finally, some large levels of changes randomly occur in folktales in small communities (similar to genetic drift). In biology, there are several methods for clustering organisms (including animal and plants). Two of these methods are 'phenetics' and “phylogenetics” clustering. It should be noted that phenetics methods are based on similarities (or differences) without attention to ancestress. In the present study we tried to clustering of 38 narratives of a very famous Iranian folktale (Sang-e Saboor). Sang-e Saboor is a tale type 894 according to the Aarne-Thompson–Uther tale type index.

In order to verify the validity of this hypothesis, in the present study, phenetics clustering analysis of 37 narratives of Sang-e Saboor in Iranian populations (Anjavi-Shirazi 2015, 317-390; Qatali 2010, 229-332; Ardalani 2003; 233-236; Elwell-Sutton 2007, 368-374; Behrangi and Dehqani 2002, 128-132; Pak 2012, 65-67; Sarfi 2008, 21-24; Fagiri 2003, 57-60; Arji 2006, 125-128; Takahara and Vakilian 2002, 97-100; Moaed-Mohseni 2002, 567-568) and a narrative from Afghanistan (Herat) was carried out (Rahmani 1998, 142-146). In the narratives used, a total of 40 features were extracted, some with more than two levels. After converting them to bi-state (zero and one) properties, a total of 53 bi-state characteristics were obtained (Table 1). The clustering was carried out using 'Euclidean distance' and analysis of 'within-group linkage'. Geographical distances between each two locations of narratives were obtain by 'Google Map'. The migration rate between two populations is a function of their geographical distance. Correlation between 'Euclidean distance' and 'geographical distance' was evaluated by Pearson correlation coefficient. Data was entered into the Statistical Package for Social Sciences software (SPSS Inc., Chicago, IL, USA) (version 11.5). A P-value less than 0.05 was considered statistical significant. All P values were two-tailed.

Table 2 should the distance matrix of each narrative with the other 37 narratives. Figure 1 shows the correlation between 'Euclidean distance' and 'geographical distance'. The correlation between geographical and Euclidean distances is statistical significant (r=+0.197, df=701, P<0.001). It should be noted that determination coefficient (r2) to be equal to 0.0388, which it means that about 3.8% of variations in 'Euclidean distances' might be interpreted by geographical distances. Given the weak correlation, the geographical distance cannot explain the differences between narratives. The study narratives were classified in two distinct clusters (Fig. 2). The first and second clusters contains 28 and 10 narratives, respectively. The narratives of the main clusters have major differences, especially in the early stages of the story. In the first cluster, it's predicted that the hero of the story will face a lot of problems in the future, while in 9 out of ten narratives of the second cluster, there is no prediction for the future of the hero of the story. On the other hand, there are similarities between some of narratives of the second cluster and another Iranian folktale (Dokhtar-e narag o torang) (Pak 2012, 173-181; Anjavi-Shirazi 2014, 19-68). It is obvious that the mentioned similarities might be a reflection of their common ancestors. Some investigators used phylogenetic clustering in order to find the evolutionary relationship between different folktales (Ross et al., 2013; O’Brien et al., 2016). Further phylogenetic studies are needed to find the possible common ancestors of Sang-e Saboor and Dokhtar-e narag o torang folktales.

By using co-word analysis, knowledge structure can be determined in a research field and its topical clusters can be identified. This research tries to study knowledge structure in mystical researches via this method and by using network analysis approaches and science visualization. The population of the current study is comprised of 1931 published articles in the field of mysticism that have been indexed in Islamic World Science Citation Center (ISC). By using scientometric and network analysis techniques, the records were retrieved and integrated. It has been used a combination of softwares, including UCINet, VosViewer and SPSS, for data analysis and mapping. Analyzing all keywords show that the most important keywords, based on frequency distribution, are top figures of mysticism: Rumi (Mulavi) and Ibn-Arabi, also Love. As in the co-word analysis, keywords’ pairs such as “Rumi-Masnavi”, “manifestation-unity of existence”, “Ibn-Arabi-unity of existence” have the most frequent co-occurrences. Analyzing lexical clusters show the most important topics related to mystical research in eleven clusters with diverse titles. Based on multidimensional scaling map, these eleven clusters are decreased into eight ones with more general topics, more conjunction and similarity. Studying the centrality and density of these clusters- which indicate maturity and development of each topic based on its keywords- in strategic diagram show that Hekmat (theosophy) or theoretical mysticism, especially from Ibn-Arabi’s point of view, not only have development ability, but also most central role among other topics.