首页> 外文OA文献 >Figure 3: (A–D) TFMN frames around “woman” (A), “man” (B) and “person” (D). Words are clustered in communities obtained via the Louvain algorithm (cf. Konstantinidis, Papadopoulos Kompatsiaris, 2017). Words in the same community of “woman” in A are plotted through a hierarchical edge-bundling visualisation in C. Positive (negative) words and links are highlighted in cyan (red). Links between positive and negative concepts are reported in purple. Semantic links between synonyms are in green. (E–F) Emotional profiles for the frames of “woman” (E) and “man” (F) indicate the fraction of concepts in a frame eliciting a certain emotion.
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Figure 3: (A–D) TFMN frames around “woman” (A), “man” (B) and “person” (D). Words are clustered in communities obtained via the Louvain algorithm (cf. Konstantinidis, Papadopoulos Kompatsiaris, 2017). Words in the same community of “woman” in A are plotted through a hierarchical edge-bundling visualisation in C. Positive (negative) words and links are highlighted in cyan (red). Links between positive and negative concepts are reported in purple. Semantic links between synonyms are in green. (E–F) Emotional profiles for the frames of “woman” (E) and “man” (F) indicate the fraction of concepts in a frame eliciting a certain emotion.

机译:图3:(a-d)“女人”(a),“man”(b)和“人”(d)周围的TFMN框架。用Louvain算法(CF.Konstantinidis,Papadopoulos&Kompatsiaris,2017年)的群体聚集在一起。在A中的“女人”中的单词通过C.正面(负)单词和链接在Cyan(红色)中突出显示了“女人”中的“女人”的单词。紫色报道了正面和消极概念之间的链接。同义词之间的语义链接是绿色的。 (E-F)“女”(e)和“人”(f)框架的情感概况表明框架中诱因某种情绪的概念的比例。

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