Adverse weather amplifies social media activity

Humanity spends an increasing proportion of its time interacting online. Scholars are intensively investigating the societal drivers and resultant impacts of this collective shift in our allocation of time and attention. Yet, the external factors that regularly shape online behavior remain markedly understudied. Do environmental factors alter rates of online activity? Here we show that adverse meteorological conditions markedly increase social media use in the United States. To do so, we employ climate econometric methods alongside over three and a half billion social media posts from tens of millions of individuals from both Facebook and Twitter between 2009 and 2016. We find that more extreme temperatures and added precipitation each independently amplify social media activity. Weather that is adverse on both the temperature and precipitation dimensions produces markedly larger increases in social media activity. On average across both platforms, compared to the temperate weather baseline, days colder than -5{\deg}C with 1.5-2cm of precipitation elevate social media activity by 35%. This effect is nearly three times the typical increase in social media activity observed on New Year's Eve in New York City. We observe meteorological effects on social media participation at both the aggregate and individual level, even accounting for individual-specific, temporal, and location-specific potential confounds

Framing COVID-19: How we conceptualize and discuss the pandemic on Twitter

Doctors and nurses in these weeks are busy in the trenches, fighting against a new invisible enemy: Covid-19. Cities are locked down and civilians are besieged in their own homes, to prevent the spreading of the virus. War-related terminology is commonly used to frame the discourse around epidemics and diseases. Arguably the discourse around the current epidemic will make use of war-related metaphors too,not only in public discourse and the media, but also in the tweets written by non-experts of mass communication. We hereby present an analysis of the discourse around #Covid-19, based on a corpus of 200k tweets posted on Twitter during March and April 2020. Using topic modelling we first analyze the topics around which the discourse can be classified. Then, we show that the WAR framing is used to talk about specific topics, such as the virus treatment, but not others, such as the effects of social distancing on the population. We then measure and compare the popularity of the WAR frame to three alternative figurative frames (MONSTER, STORM and TSUNAMI) and a literal frame used as control (FAMILY). The results show that while the FAMILY literal frame covers a wider portion of the corpus, among the figurative framings WAR is the most frequently used, and thus arguably the most conventional one. However, we conclude, this frame is not apt to elaborate the discourse around many aspects involved in the current situation. Therefore, we conclude, in line with previous suggestions, a plethora of framing options, or a metaphor menu, may facilitate the communication of various aspects involved in the Covid-19-related discourse on the social media, and thus support civilians in the expression of their feelings, opinions and ideas during the current pandemic.Comment: 41 pages, 6 figure

A Study on the Translation of Ball Lightning from the Perspective of Eco-Translatology

As a renowned contemporary hard science fiction novelist from China, Liu Cixin has secured his standing in the global literature scene by winning the Best Novel Award at the 73rd Hugo Awards for The Three-Body Problem. This historical triumph marked an unprecedented event for Chinese and Asian scientific authors. Following this achievement, many translation scholars buried themselves in the English translation of Liu Cixin's The Three-Body Problem through various translation theories, such as Skopos Theory and Relevance Theory. However, limited scholars’ attention has been dedicated to another famous work of Liu’s, Ball Lightning, nor the translation process of this novel. To fill this gap in the field of translation studies, this research focuses on the translation of Ball Lightning, particularly the English translation by Joel Martinsen. This study aims to reveal some hard science characteristics and methods of Joel’s translation through some case studies. Firstly, it will examine the translation ecological environment of Ball Lightning from the source and target language. Further, the study will analyse Joel Martinsen’s adaptation strategies within the framework of eco-translatology, evaluating the translator’s proficiency. Finally, this research will assess the translation of Ball Lightning from three perspectives: the linguistic, the cultural, and the communicative aspects. The concluding part of this thesis offers a detailed critique of Ball Lightning through eco-translatology, specifically focusing on its principles of adaptation and selection

Social media mental health analysis framework through applied computational approaches

Studies have shown that mental illness burdens not only public health and productivity but also established market economies throughout the world. However, mental disorders are difficult to diagnose and monitor through traditional methods, which heavily rely on interviews, questionnaires and surveys, resulting in high under-diagnosis and under-treatment rates. The increasing use of online social media, such as Facebook and Twitter, is now a common part of people’s everyday life. The continuous and real-time user-generated content often reflects feelings, opinions, social status and behaviours of individuals, creating an unprecedented wealth of person-specific information. With advances in data science, social media has already been increasingly employed in population health monitoring and more recently mental health applications to understand mental disorders as well as to develop online screening and intervention tools. However, existing research efforts are still in their infancy, primarily aimed at highlighting the potential of employing social media in mental health research. The majority of work is developed on ad hoc datasets and lacks a systematic research pipeline. [Continues.]</div

Have media texts become more humorous?

As a research topic, humour has drawn much attention from multiple disciplines including linguistics. Based on Engelthaler & Hills’ (2018) humour scale, this study developed a measure named Humour Index (HMI) to quantify the degree of humour of texts. This measure was applied to examine the diachronic changes in the degree of humour of American newspapers and magazines across a time span of 118 years (1900-2017) with the use of texts from Corpus of Historical American English (COHA). Besides, the study also discussed the contributions of different types of words to the degree of humour in the two genres. The results show significant uptrends in the degree of humour of both newspapers and magazines in the examined period. Moreover, derogatory and offensive words are found to be less frequently used than other categories of words in both genres. This study provides both theoretical and methodological implications for humour studies and claims or hypotheses of previous research, such as infotainment and linguistic positivity bias

Social Media Meets Big Urban Data: A Case Study of Urban Waterlogging Analysis

With the design and development of smart cities, opportunities as well as challenges arise at the moment. For this purpose, lots of data need to be obtained. Nevertheless, circumstances vary in different cities due to the variant infrastructures and populations, which leads to the data sparsity. In this paper, we propose a transfer learning method for urban waterlogging disaster analysis, which provides the basis for traffic management agencies to generate proactive traffic operation strategies in order to alleviate congestion. Existing work on urban waterlogging mostly relies on past and current conditions, as well as sensors and cameras, while there may not be a sufficient number of sensors to cover the relevant areas of a city. To this end, it would be helpful if we could transfer waterlogging. We examine whether it is possible to use the copious amounts of information from social media and satellite data to improve urban waterlogging analysis. Moreover, we analyze the correlation between severity, road networks, terrain, and precipitation. Moreover, we use a multiview discriminant transfer learning method to transfer knowledge to small cities. Experimental results involving cities in China and India show that our proposed framework is effective

Research on Phraseology Across Continents

The second volume of the IDP series contains papers by phraseologists from five continents: Europe, Australia, North America, South America and Asia, which were written within the framework of the project Intercontinental Dialogue on Phraseology, prepared and coordinated by Joanna Szerszunowicz, conducted by the University of Bialystok in cooperation with Kwansei Gakuin University in Japan. The book consists of the following parts: Dialogue on Phraseology, General and Corpus Linguistics & Phraseology, Lexicography & Phraseology, Contrastive Linguistics, Translation & Phraseology, Literature, Cultural Studies, Education & Phraseology. Dialogue contains two papers written by widely recognised phraseologists: professor Anita Naciscione from Latvia and professor Irine Goshkheteliani.The volume has been financed by the Philological Department of the University of Bialysto