Em um artigo publicado no Nightingale , arXiv e ResearchGate, ele apresentou o primeiro mapa de rede visual delineando os padraµes ocultos, enredos e relacionamentos de personagens na sanãrie de fantasia.
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)
O mapa social de The Witcher. Os personagens são representados por nós, seu tamanho corresponde ao seu grau de na³ (o número de conexões), e sua coloração e rotulagem mostram aqueles indivíduos que já apareceram na primeira temporada da adaptação para TV Netflix de The Witcher (vermelho) do resto da sanãrie. caracteres ainda a aparecer (cinza). Os links de rede são proporcionais ao número de vezes que dois personagens foram mencionados a uma distância de cinco frases um do outro no romance. Crédito: Milan Janosov.
"The Witcher", uma sanãrie de romances de fantasia de Andrzej Sapkowski, tornou-se cada vez mais popular, após o lana§amento de vários videogames e uma sanãrie derivada da Netflix. A última temporada do programa, lana§ada na Netflix em dezembro de 2021, foi assistida por usuários em todo o mundo por 2,2 bilhaµes de minutos apenas em sua semana de estreia.
Mila¡n Janosov , cientista-chefe da Datopolis com Ph.D. em Network Science da Central European University recentemente tentou resumir o enredo e as relações dos personagens em "The Witcher" usando a ciência da rede . Em um artigo publicado no Nightingale , arXiv e ResearchGate, ele apresentou o primeiro mapa de rede visual delineando os padraµes ocultos, enredos e relacionamentos de personagens na sanãrie de fantasia.
"Comecei a ler 'The Witcher' no inicio do ano passado, logo depois que me viciei na sanãrie da Netflix, e a história me atraiu", disse Janosov ao TechXplore. "Foi uma experiência um pouco semelhante a assistir 'Game of Thrones'. alguns anos atrás, que também inspirou um dos meus artigos de pesquisa . Quando eu estava prestes a terminar de assistir a nova temporada de Witcher, comecei a me perguntar como poderia tirar mais proveito disso."
Embora os videogames "The Witcher" também sejam altamente populares e ica´nicos, Janosov foi mais atraado pelas histórias e relacionamentos descritos nos livros e na sanãrie Netflix. Em uma busca para entender o mundo da sanãrie ica´nica com mais profundidade, ele decidiu criar um mapa social de 'The Witcher'."
O primeiro passo para sua pesquisa foi coletar dados que ele poderia usar para criar o mapa da rede. Ele começou olhando as legendas da sanãrie da Netflix, mas logo percebeu que precisaria de mais do que isso e decidiu analisar todo o texto da sanãrie de livros também.
"Para construir uma rede, eu também precisava de uma lista completa dos personagens que apareceram na sanãrie", disse Janosov. "Depois de coletar essas informações iniciais, meu trabalho era bastante simples. Escrevi um programa de computador que examinava cada frase de todos os livros e anotava cada vez que combinava o nome de um personagem em uma frase."
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Usando seu programa de computador, Janosov derivou as menções para cada caractere em frases. Isso permitiu que ele determinasse o quanto pra³ximos ou distantes dois personagens estavam, em termos de quantas vezes eles eram mencionados em partes semelhantes dos textos (por exemplo, se dois personagens foram mencionados na mesma frase, duas frases separadas e assim por diante).
“Acontece que essas proximidades são indicadores muito bons de se dois personagens realmente se conheceram ou foram apresentados nas mesmas tramasâ€, disse Janosov.
Apa³s observar a proximidade entre as menções dos personagens, Janosov definiu os elementos em sua rede. Mais especificamente, ele decidiu representar cada caractere com um na³, ligando nosquando os personagens eram mencionados no mesmo "contexto" ou parte do texto.
"Embora o contexto seja relativamente fa¡cil de interpretar para humanos, para um computador, não étão simples", explicou Janosov. "Então, para capturar o contexto dos personagens mencionados, assumi que dois personagens foram mencionados no mesmo contexto, já que não foram mencionados a mais de cinco frases um do outro. Embora o número cinco seja um pouco arbitra¡rio, foi escolhido por uma questãode simplicidade (e facilidade de TOC), porque três, quatro ou mesmo seis distâncias de frases também levam a resultados muito semelhantes, também permanecendo consistentes, por exemplo, com os comprimentos de para¡grafo tapicos em texto escrito."
O artigo de Janosov éum exemplo valioso de como a ciência de rede pode ser usada para revelar padraµes ocultos em grandes quantidades de dados não estruturados, como textos, romances ou roteiros de filmes. Depois de ler livros ou outros textos com milhares de pa¡ginas, os humanos podem ter uma ideia geral de como uma história éestruturada. No entanto, eles geralmente não sera£o capazes de memorizar todos os personagens e lembrar de todos os detalhes da trama.
Se eles desenhassem um mapa da história, portanto, esse mapa provavelmente seria tendencioso. Em contraste, as ferramentas de ciência de rede podem ajudar a resumir uma saga ou sanãrie de livros de forma quantitativa e objetiva.
"Fiquei surpreso e animado ao ver os diferentes lotes agrupados em comunidades de rede", disse Janosov. "Vocaª conhece aquele tipo de momento Eureka quando de repente tudo comea§a a fazer sentido - quem conheceu quem, quem estãojunto, onde os principais conflitos e enredos menores se desenrolam, etc., quase como em um filme de detetive. , o canãtico pode perguntar - por que nos importaraamos tanto com um romance de fantasia? Embora o exemplo de 'The Witcher' seja certamente divertido, de fato não parece ter essa importa¢ncia prática crucial no inacio."
Embora o mapa de rede de "The Witcher" resultante deste estudo e outros mapas que Janosov criou no passado sejam aºnicos e interessantes, seu trabalho éapenas um exemplo de como a ciência de rede pode ser implementada no mundo real. De fato, ferramentas semelhantes de análise de dados também podem ser usadas para resumir outras redes no mundo real.
"Em nossas vidas dia¡rias, estamos cercados por redes sociais: nossos amigos nas madias sociais, nossos colegas de trabalho, amigos da escola, famalia, esportes e hobbies e muito mais", disse Janosov. "Todos esses sistemas sociais estãoentrelaa§ados por redes das quais quase sempre temos apenas uma compreensão parcial e subjetiva. que pode nos ajudar a entender melhor essas redes sociais das quais participamos diariamente, assim como ajudou a limpar a nanãvoa em torno de 'The Witcher'."
Ferramentas de ciência de rede como as empregadas por Janosov também podem ser aplicadas (ou já estãoem uso) em uma sanãrie de configurações do mundo real. Por exemplo, eles podem ser usados ​​por especialistas de RH para projetar melhores ambientes de trabalho ou melhorar a colaboração entre colegas de trabalho, por organizações cientaficas para otimizar o compartilhamento de financiamento de pesquisa entre diferentes grupos de pesquisa ou atémesmo para analisar e melhorar o comanãrcio internacional e as telecomunicações.
"Como o Oscar estãochegando no pra³ximo maªs, agora estou pensando em revisitar minha pesquisa anterior capturando o papel da sorte no sucesso dos filmes e da música , para ver o quanto a sorte conta este ano", acrescentou Janosov.