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Sumin Zhao

dblp:198/5564 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Information extraction and text analysis · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Information extraction and text analysis › lexical semantics
emoji semantics
0.812024
Semantics and Sentiment: Cross-lingual Variations in Emoji Use · EMNLP 2024
Natural language and speech › Information extraction and text analysis
sentiment analysis
0.812024
Semantics and Sentiment: Cross-lingual Variations in Emoji Use · EMNLP 2024

Methods — techniques the papers use, named apart from their topics

cross-lingual corpus analysis · 0.8
YearPublicationVenuePosition
2024 Semantics and Sentiment: Cross-lingual Variations in Emoji Use
abstract
Over the past decade, the use of emojis in social media has seen a rapid increase.Despite their popularity and image-grounded nature, previous studies have found that people interpret emojis inconsistently when presented in context and in isolation.In this work, we explore whether emoji semantics differ across languages and how semantics interacts with sentiment in emoji use across languages.To do so, we developed a corpus containing the literal meanings for a set of emojis, as defined by L1 speakers in English, Portuguese and Chinese.We then use these definitions to assess whether speakers of different languages agree on whether an emoji is being used literally or figuratively in the context where they are grounded in, as well as whether this literal and figurative use correlates with the sentiment of the context itself.We found that there were varying levels of disagreement on the definition for each emoji but that these stayed fairly consistent across languages.We also demonstrated a correlation between the sentiment of a tweet and the figurative use of an emoji, providing theoretical underpinnings for empirical results in NLP tasks, particularly offering insights that can benefit sentiment analysis models.
Giulio Zhou, Sydelle De Souza, Ella Markham, Oghenetekevwe Kwakpovwe, Sumin Zhao
EMNLP5