Lexicon in opinion mining and sentiment analysis is defined as (select one best answer):

Question

BlackTom AI · Accepted Answer

In this question about lexicon in opinion mining and sentiment analysis, we need to evaluate what each option implies about the role of a lexicon.
Option 1: 'Mapping of words into sentiment by polarity and intensity' This aligns with the core function of a sentiment lexicon, which assigns each word a sentiment polarity (positive/negative/neutral) and often an intensity or strength score to reflect how strongly the word conveys sentiment.
Option 2: 'Vocabulary of text corpus' While a vocabulary represents the set of distinct words used in a corpus, it does not by itself encode sentiment information, polarity, or intensity. A lexicon goes beyond simply listing words to attaching sentiment values to them.
From a conceptual standpoint, lexicons are designed to annotate words with sentiment-related attributes so they can be aggregated to estimate the overall sentiment of texts. The idea of simply listing vocabulary misses this essential sentiment mapping aspect.
If we contrast the two options, the first emphasizes the sentiment labeling aspect that lexicons provide, whereas the second describes a general lexical inventory without sentiment semantics. Therefore, the first option captures the intended definition most accurately.
Additionally, recognizing polarity and intensity enables more nuanced sentiment analysis, including handling words with varying strengths, negations, and intensity modifiers. The second option would be insufficient for such analyses, as it lacks the sentiment annotation component.
Overall, the statement in Option 1 correctly characterizes a sentiment lexicon's purpose and content, while Option 2 describes a broader, non-sentiment-specific concept of vocabulary.

Lexicon in opinion mining and sentiment analysis is defined as (select one best answer):单项选择题

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