Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Crowdsourcing a Word-Emotion Association Lexicon   Even though considerable attention has been given to the polarity of words
(positive and negative) and the creation of large polarity lexicons, research
in emotion analysis has had to rely on limited and small emotion lexicons. In
this paper we show how the combined strength and wisdom of the crowds can be
used to generate a large, high-quality, word-emotion and word-polarity
association lexicon quickly and inexpensively. We enumerate the challenges in
emotion annotation in a crowdsourcing scenario and propose solutions to address
them. Most notably, in addition to questions about emotions associated with
terms, we show how the inclusion of a word choice question can discourage
malicious data entry, help identify instances where the annotator may not be
familiar with the target term (allowing us to reject such annotations), and
help obtain annotations at sense level (rather than at word level). We
conducted experiments on how to formulate the emotion-annotation questions, and
show that asking if a term is associated with an emotion leads to markedly
higher inter-annotator agreement than that obtained by asking if a term evokes
an emotion.

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The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
20
The categories of this paper are: acc-phys
18
The categories of this paper are: econ
12
The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga
34
The categories of this paper are: chem-ph
30
The categories of this paper are: q-alg
8
The categories of this paper are: hep-ex
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The categories of this paper are: eess
10
The categories of this paper are: q-bio
11
The categories of this paper are: hep-lat
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The categories of this paper are: astro-ph
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The categories of this paper are: stat
33
The categories of this paper are: plasm-ph
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The categories of this paper are: chao-dyn