NLP - LISAC at S em E val-2023 Task 9: Multilingual Tweet Intimacy Analysis via a Transformer-based Approach and Data Augmentation (2023)

Abstract: This paper presents our system and findings for SemEval 2023 Task 9 Tweet Intimacy Analysis. The main objective of this task was to predict the intimacy of tweets in 10 languages. Our submitted model (ranked 28/45) consists of a transformer-based approach with data augmentation via machine translation.

## introduction according to the cambridge dictionary 1 , intimacy is things that are said or done only by people who have a close relationship with each other. tweet intimacy is a term that is used to describe the relationship between twitter users and the way they interact with one another through the social media platform. it refers to the level of personal connection and familiarity that exists between individuals who engage with each other on twitter. this can be determined by various factors, such as the frequency of interaction, the types of content shared, and the use of personal language or inside jokes. a high level of tweet intimacy suggests that the individuals have a strong, personal relationship, while a low level of tweet intimacy indicates more casual or impersonal interactions. in this paper, we present our findings on se-meval 2023 task 9: multilingual tweet intimacy analysis @xcite . our method consists of a transformer-based approach @xcite along with data augmentation. the rest of the paper is structured in the following manner: section 2 provides the main objective of the task. section 3 describes our system. section 4 details the experiments. and finally, section 5 concludes this paper. ## system description to tackle the semeval 2023 task 9: multilingual tweet intimacy analysis, we have fine-tuned a transformer-based model on an augmented training dataset. the different steps of our system are described as follows: ## experimental results we experimented our model on the semeval 2023 task 9: multilingual tweet intimacy analysis dataset. the experiment has been conducted in google colab environment foot_1 , the following libraries: transformers -hugging face foot_2 @xcite , and keras foot_3 were used to train and to assess the performance of our model. ## conclusion tweet intimacy refers to the level of personal connection and emotional closeness that individuals express through their tweets. research has shown that tweet intimacy can be influenced by factors such as the language used, the content of the tweets, and the relationship between the tweeter and their audience @xcite . in this paper, we described our approach for tackling semeval 2023 task 9: multilingual tweet intimacy analysis. our submitted system consisted of a transformer-based approach along with data augmentation and secured the 28th position among a total of 45 teams. as social media continues to play an increasingly important role in our daily lives, it is likely that research on tweet intimacy will continue to be an important area of investigation.