Proceedings of the 7th International Workshop on Social Media World Sensors最新文献

Invited Talk: On Proactive Sentence Specific Popularity Forecasting 特邀演讲:主动句具体流行度预测

Proceedings of the 7th International Workshop on Social Media World Sensors Pub Date : 2022-06-28 DOI: 10.1145/3544795.3544849

Sayar Ghosh Roy

引用次数: 0

Classifying Anti-Mask Tweets into Misclassification vs. Rejection: A Year-Long Study 将反面具推文分类为错误分类与拒绝:一项为期一年的研究

Proceedings of the 7th International Workshop on Social Media World Sensors Pub Date : 2022-06-28 DOI: 10.1145/3544795.3544845

Julia Warnken, S. Gokhale

{"title":"Classifying Anti-Mask Tweets into Misclassification vs. Rejection: A Year-Long Study","authors":"Julia Warnken, S. Gokhale","doi":"10.1145/3544795.3544845","DOIUrl":"https://doi.org/10.1145/3544795.3544845","url":null,"abstract":"The debate over masks has played out vigorously over social media platforms such as Twitter over the course of the Covid-19 pandemic. Anti-maskers oppose the use of face masks on two philosophical grounds. First, they question their effectiveness and second, they reject them as an infringement of their personal liberties and freedoms. Both these narratives can be damaging in their own respective ways; misinformation can mislead people to abandon this simple public health measure, and rejection can incite unrest, disobedience and violence. Different policies, ranging from completely removing the tweet to simply placing a warning label, may be applied to these two types of anti-mask tweets to mitigate their damage. To facilitate these differentiated policy decisions, driven by the state of the pandemic and the surrounding social and political circumstances, this paper proposes a machine learning approach to separate anti-mask tweets into misinformation and rejection. Linguistic, social, auxiliary, and sentiment features are extracted from this corpus of tweets collected over the first year. A combination of these features is used to train ensemble and neural network classifiers. The results show that our machine learning framework can separate between misinformation and rejection tweets with a F1-score of around 0.90. These results are noteworthy because the framework can classify between two groups of tweets that share a common overall theme of anti-masking yet have only subtle differences. Moreover, the data collected over a period of one year implies that this separation is achieved even when the anti-masking rhetoric is embedded in widely varying social and political contexts.","PeriodicalId":103807,"journal":{"name":"Proceedings of the 7th International Workshop on Social Media World Sensors","volume":"204 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116186569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

SIDEWAYS-2022 @ HT-2022: 7th International Workshop on Social Media World Sensors sidesides -2022 @ HT-2022:第七届社交媒体世界传感器国际研讨会

Proceedings of the 7th International Workshop on Social Media World Sensors Pub Date : 2022-06-28 DOI: 10.1145/3544795.3544844

Mario Cataldi, Luigi Di Caro, C. Schifanella

引用次数: 0

Towards a Cross-Domain Context-Aware Recommender of Optimal Experiences 面向跨领域上下文感知的最佳体验推荐

Proceedings of the 7th International Workshop on Social Media World Sensors Pub Date : 2022-06-28 DOI: 10.1145/3544795.3544853

Sabrina Villata, F. Cena

{"title":"Towards a Cross-Domain Context-Aware Recommender of Optimal Experiences","authors":"Sabrina Villata, F. Cena","doi":"10.1145/3544795.3544853","DOIUrl":"https://doi.org/10.1145/3544795.3544853","url":null,"abstract":"Nowadays, many people suffer from depression, anxiety disorder, stress and bad emotions. Most of the times, the causes are a chaotic lifestyle, stressful jobs and activities, wrong habits and a permanent sense of uncertainty. Therefore, well-being plays an increasingly important role in people’s lives, as it can help them to prevent chronic disease and long-term illnesses. However, well-being does not concern only healthy lifestyle, rather it is necessary to consider also mental health and interior happiness. In this position paper, we propose the idea of FlowMe, a cross-domain context-aware recommender system of optimal experiences, i.e. situations when people report feelings of deep enjoyment, forgetting the passage of time and external worries, and reaching an inner harmony on which their general happiness depends. In our perspective, FlowMe could be connected to different IoT devices and applications, such as social media, to collect data from the users and learn their mood, behaviour and habits, in order to suggest personalized optimal experiences when they are feeling a negative emotion. Also, the system will recognise when the user is in the flow doing a certain activity. FlowMe takes into account optimal experiences from various domains, considering users’ preferences and their context.","PeriodicalId":103807,"journal":{"name":"Proceedings of the 7th International Workshop on Social Media World Sensors","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124529016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A New Corpus and Lexicon for Offensive Tamazight Language Detection 一种新的攻击性塔马兹语检测语料库和词典

Proceedings of the 7th International Workshop on Social Media World Sensors Pub Date : 2022-06-28 DOI: 10.1145/3544795.3544852

K. Abainia, Kenza Kara, Tassadit Hamouni

引用次数: 3

Analysis and Visualization of the Sense Of Place from Twitter Data 基于Twitter数据的地点感分析与可视化

Proceedings of the 7th International Workshop on Social Media World Sensors Pub Date : 2022-06-28 DOI: 10.1145/3544795.3544854

Michele Lanotte, Giovanni Siracusa

引用次数: 0