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相关论文: Overview of Memotion 3: Sentiment and Emotion Anal…

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Memes are the new-age conveyance mechanism for humor on social media sites. Memes often include an image and some text. Memes can be used to promote disinformation or hatred, thus it is crucial to investigate in details. We introduce…

This paper presents a robust solution to the Memotion 3.0 Shared Task. The goal of this task is to classify the emotion and the corresponding intensity expressed by memes, which are usually in the form of images with short captions on…

计算与语言 · 计算机科学 2023-02-15 Yu-Chien Tang , Kuang-Da Wang , Ting-Yun Ou , Wen-Chih Peng

Information on social media comprises of various modalities such as textual, visual and audio. NLP and Computer Vision communities often leverage only one prominent modality in isolation to study social media. However, the computational…

计算机视觉与模式识别 · 计算机科学 2020-08-11 Chhavi Sharma , Deepesh Bhageria , William Scott , Srinivas PYKL , Amitava Das , Tanmoy Chakraborty , Viswanath Pulabaigari , Bjorn Gamback

Memes have become an ubiquitous social media entity and the processing and analysis of suchmultimodal data is currently an active area of research. This paper presents our work on theMemotion Analysis shared task of SemEval 2020, which…

计算机视觉与模式识别 · 计算机科学 2020-08-04 Pradyumna Gupta , Himanshu Gupta , Aman Sinha

Memes are one of the most ubiquitous forms of social media communication. The study and processing of memes, which are intrinsically multimedia, is a popular topic right now. The study presented in this research is based on the Memotion…

计算与语言 · 计算机科学 2021-12-23 Nayan Varma Alluri , Neeli Dheeraj Krishna

Social media is abundant in visual and textual information presented together or in isolation. Memes are the most popular form, belonging to the former class. In this paper, we present our approaches for the Memotion Analysis problem as…

计算与语言 · 计算机科学 2020-07-23 Vishal Keswani , Sakshi Singh , Suryansh Agarwal , Ashutosh Modi

Sentiment Analysis is the process of deciphering what a sentence emotes and classifying them as either positive, negative, or neutral. In recent times, India has seen a huge influx in the number of active social media users and this has led…

计算与语言 · 计算机科学 2020-09-07 Subhra Jyoti Baroi , Nivedita Singh , Ringki Das , Thoudam Doren Singh

We explore the task of sentiment analysis on Hinglish (code-mixed Hindi-English) tweets as participants of Task 9 of the SemEval-2020 competition, known as the SentiMix task. We had two main approaches: 1) applying transfer learning by…

计算与语言 · 计算机科学 2020-08-05 Vinay Gopalan , Mark Hopkins

Memes are prevalent on the internet and continue to grow and evolve alongside our culture. An automatic understanding of memes propagating on the internet can shed light on the general sentiment and cultural attitudes of people. In this…

计算与语言 · 计算机科学 2022-04-05 Ana-Maria Bucur , Adrian Cosma , Ioan-Bogdan Iordache

Users from the online environment can create different ways of expressing their thoughts, opinions, or conception of amusement. Internet memes were created specifically for these situations. Their main purpose is to transmit ideas by using…

Problems involving code-mixed language are often plagued by a lack of resources and an absence of materials to perform sophisticated transfer learning with. In this paper we describe our submission to the Sentimix Hindi-English task…

计算与语言 · 计算机科学 2020-07-24 Aditya Srivastava , V. Harsha Vardhan

In this paper, we present the results of the SemEval-2020 Task 9 on Sentiment Analysis of Code-Mixed Tweets (SentiMix 2020). We also release and describe our Hinglish (Hindi-English) and Spanglish (Spanish-English) corpora annotated with…

Hate speech detection in Devanagari-scripted social media memes presents compounded challenges: multimodal content structure, script-specific linguistic complexity, and extreme data scarcity in low-resource settings. This paper presents our…

计算与语言 · 计算机科学 2026-04-17 Samir Wagle , Reewaj Khanal , Abiral Adhikari

In today's interconnected and multilingual world, code-mixing of languages on social media is a common occurrence. While many Natural Language Processing (NLP) tasks like sentiment analysis are mature and well designed for monolingual text,…

计算与语言 · 计算机科学 2020-09-01 Laksh Advani , Clement Lu , Suraj Maharjan

This paper describes our contribution to the SemEval-2020 Task 9 on Sentiment Analysis for Code-mixed Social Media Text. We investigated two approaches to solve the task of Hinglish sentiment analysis. The first approach uses cross-lingual…

计算与语言 · 计算机科学 2020-10-22 Pranaydeep Singh , Els Lefever

This paper describes the participation of our NUAA-QMUL-AIIT team in the Memotion 3 shared task on meme emotion analysis. We propose a novel multi-modal fusion method, Squeeze-and-Excitation Fusion (SEFusion), and embed it into our system…

计算与语言 · 计算机科学 2023-02-17 Xiaoyu Guo , Jing Ma , Arkaitz Zubiaga

In this article, we describe the system that we used for the memotion analysis challenge, which is Task 8 of SemEval-2020. This challenge had three subtasks where affect based sentiment classification of the memes was required along with…

计算机视觉与模式识别 · 计算机科学 2020-05-25 Sourya Dipta Das , Soumil Mandal

Today's Internet is awash in memes as they are humorous, satirical, or ironic which make people laugh. According to a survey, 33% of social media users in age bracket [13-35] send memes every day, whereas more than 50% send every week. Some…

计算与语言 · 计算机科学 2021-03-24 Shraman Pramanick , Md Shad Akhtar , Tanmoy Chakraborty

This paper discusses the results obtained for different techniques applied for performing the sentiment analysis of social media (Twitter) code-mixed text written in Hinglish. The various stages involved in performing the sentiment analysis…

计算与语言 · 计算机科学 2021-02-25 Gaurav Singh

In recent years, the growing ubiquity of Internet memes on social media platforms, such as Facebook, Instagram, and Twitter, has become a topic of immense interest. However, the classification and recognition of memes is much more…

计算与语言 · 计算机科学 2020-07-29 Li Yuan , Jin Wang , Xuejie Zhang
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