Analyzing the Evolution of Social Concepts Using Temporal Embedding Models
سال انتشار: 1404
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 33
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شناسه ملی سند علمی:
SETBCONF04_210
تاریخ نمایه سازی: 2 مرداد 1404
چکیده مقاله:
The meanings of social concepts are not fixed—they evolve in response to cultural, political, and technological changes. Capturing this semantic evolution is essential for understanding shifts in public discourse and societal values. Traditional word embedding models like Word۲Vec provide static representations and are thus unable to reflect temporal variations in meaning. In this paper, we introduce a dynamic embedding-based framework to trace the semantic trajectories of key social concepts—such as freedom, identity, and equality—across multiple decades. Using temporally segmented text corpora from ۱۹۵۰ to ۲۰۲۰, we train time-aware embeddings to visualize and quantify changes in meaning over time. Our results reveal significant and interpretable semantic shifts, often aligning with major historical events and social movements. This research underscores the potential of temporal embeddings as a powerful tool for computational social science and digital humanities.
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نویسندگان
Seyedeh Samira Rabinataj
Department of Humanities, University of Turin, Turin, Italy