The impact of toxic trolling comments on anti-vaccine YouTube videos.

Anti-vaccine trolling on video-hosting websites hinders efforts to increase vaccination rates by using toxic language and threatening claims to intimidate people and promote vaccine hesitancy. However, there is a shortage of research investigating the effects of toxic messages on these platforms. This study focused on YouTube anti-vaccine videos and examined the relationship between toxicity and fear in the comment section of these videos. We discovered that highly liked toxic comments were associated with a significant level of fear in subsequent comments. Moreover, we found complex patterns of contagion between toxicity and fear in the comments. These findings suggest that initial troll comments can evoke negative emotions in viewers, potentially fueling vaccine hesitancy. Our research bears essential implications for managing public health messaging and online communities, particularly in moderating fear-mongering messages about vaccines on social media.

Aggressive behaviour of anti-vaxxers and their toxic replies in English and Japanese.

The anti-vaccine movement has gained traction in many countries since the COVID-19 pandemic began. However, their aggressive behaviour through replies on Twitter-a form of directed messaging that can be sent beyond follow-follower relationships-is less understood, and even less is known about the language use differences of this behaviour. We conducted a comparative study of anti-vaxxers' aggressive behaviours by analysing a longitudinal dataset of COVID-19 tweets in English and Japanese. We found two common features across these languages. First, anti-vaxxers most actively transmit targeted messages or replies to users with different beliefs, especially to neutral accounts, with significantly toxic and negative language, and these replies are often directed to posts about vaccine operations. Second, influential users with many followers and verified accounts are more likely to receive the most toxic replies from the anti-vaxxers. However, pro-vaccine accounts with a few followers receive highly toxic replies in English, which is different from the Japanese case. These results provide insights into both language-dependent and independent countermeasures against anti-vaxxers' aggressive behaviour.

Development of the Japanese Version of the Linguistic Inquiry and Word Count Dictionary 2015.

The Linguistic Inquiry and Word Count Dictionary 2015 (LIWC2015) is a standard text analysis dictionary that quantifies the linguistic and psychometric properties of English words. A Japanese version of the LIWC2015 dictionary (J-LIWC2015) has been expected in the fields of natural language processing and cross-cultural research. This study aims to create the J-LIWC2015 through systematic investigations of the original dictionary and Japanese corpora. The entire LIWC2015 dictionary was initially subjected to human and machine translation into Japanese. After verifying the frequency of use of the words in large corpora, frequent words and phrases that are unique to Japanese were added to the dictionary, followed by recategorization by psychologists. The updated dictionary indicated good internal consistency, semantic equivalence with the original LIWC2015 dictionary, and good construct validity in each category. The evidence suggests that the J-LIWC2015 dictionary is a powerful research tool in computational social science to scrutinize the psychological processes behind Japanese texts and promote standardized cross-cultural investigations in combination with LIWC dictionaries in different languages.

Characterizing the roles of bots on Twitter during the COVID-19 infodemic.

An infodemic is an emerging phenomenon caused by an overabundance of information online. This proliferation of information makes it difficult for the public to distinguish trustworthy news and credible information from untrustworthy sites and non-credible sources. The perils of an infodemic debuted with the outbreak of the COVID-19 pandemic and bots (i.e., automated accounts controlled by a set of algorithms) that are suspected of spreading the infodemic. Although previous research has revealed that bots played a central role in spreading misinformation during major political events, how bots behavior during the infodemic is unclear. In this paper, we examined the roles of bots in the case of the COVID-19 infodemic and the diffusion of non-credible information such as "5G" and "Bill Gates" conspiracy theories and content related to "Trump" and "WHO" by analyzing retweet networks and retweeted items. We show the segregated topology of their retweet networks, which indicates that right-wing self-media accounts and conspiracy theorists may lead to this opinion cleavage, while malicious bots might favor amplification of the diffusion of non-credible information. Although the basic influence of information diffusion could be larger in human users than bots, the effects of bots are non-negligible under an infodemic situation. Supplementary Information: The online version contains supplementary material available at 10.1007/s42001-021-00139-3.

Correction to: Characterizing the roles of bots on Twitter during the COVID­19 infodemic.

[This corrects the article DOI: 10.1007/s42001-021-00139-3.].

Morality-Based Assertion and Homophily on Social Media: A Cultural Comparison Between English and Japanese Languages.

Moral psychology is a domain that deals with moral identity, appraisals and emotions. Previous work has primarily focused on moral development and the associated role of culture. Knowing that language is an inherent element of a culture, we used the social media platform Twitter to compare moral behaviors of Japanese tweets with English tweets. The five basic moral foundations, i.e., Care, Fairness, Ingroup, Authority, and Purity, along with the associated emotional valence were compared between English and Japanese tweets. The tweets from Japanese users depicted relatively higher Fairness, Ingroup, and Purity, whereas English tweets expressed more positive emotions for all moral dimensions. Considering moral similarities in connecting users on social media, we quantified homophily concerning different moral dimensions using our proposed method. The moral dimensions Care, Authority, and Purity for English and Ingroup, Authority and Purity for Japanese depicted homophily on Twitter. Overall, our study uncovers the underlying cultural differences with respect to moral behavior in English- and Japanese-speaking users.

Appraisal of the Fairness Moral Foundation Predicts the Language Use Involving Moral Issues on Twitter Among Japanese.

Moral appraisals are found to be associated with a person's individual differences (e.g., political ideology), and the effects of individual differences on language use have been studied within the framework of the Moral Foundations Theory (MFT). However, the relationship between one's moral concern and the use of language involving morality on social media is not self-evident. The present exploratory study investigated that relationship using the MFT. Participants' tweets and self-reported responses to the questionnaire were collected to measure the degree of their appraisals according to the five foundations of the MFT. The Japanese version of the Moral Foundations Dictionary (J-MFD) was used to quantify the number of words in tweets relevant to the MFT's five moral foundations. The results showed that endorsement of the Fairness and Authority foundations predicted the word frequency in the J-MFD across all five foundations. The findings suggest that the trade-off relationship between the Fairness and Authority foundations plays a key role in online language communication. The implications and future directions to scrutinize that foundation are discussed.

Development and validation of the Japanese Moral Foundations Dictionary.

The Moral Foundations Dictionary (MFD) is a useful tool for applying the conceptual framework developed in Moral Foundations Theory and quantifying the moral meanings implicated in the linguistic information people convey. However, the applicability of the MFD is limited because it is available only in English. Translated versions of the MFD are therefore needed to study morality across various cultures, including non-Western cultures. The contribution of this paper is two-fold. We developed the first Japanese version of the MFD (referred to as the J-MFD) using a semi-automated method-this serves as a reference when translating the MFD into other languages. We next tested the validity of the J-MFD by analyzing open-ended written texts about the situations that Japanese participants thought followed and violated the five moral foundations. We found that the J-MFD correctly categorized the Japanese participants' descriptions into the corresponding moral foundations, and that the Moral Foundations Questionnaire (MFQ) scores correlated with the frequency of situations, of total words, and of J-MFD words in the participants' descriptions for the Harm and Fairness foundations. The J-MFD can be used to study morality unique to the Japanese and also multicultural comparisons in moral behavior.

Acoustic sequences in non-human animals: a tutorial review and prospectus.

Animal acoustic communication often takes the form of complex sequences, made up of multiple distinct acoustic units. Apart from the well-known example of birdsong, other animals such as insects, amphibians, and mammals (including bats, rodents, primates, and cetaceans) also generate complex acoustic sequences. Occasionally, such as with birdsong, the adaptive role of these sequences seems clear (e.g. mate attraction and territorial defence). More often however, researchers have only begun to characterise - let alone understand - the significance and meaning of acoustic sequences. Hypotheses abound, but there is little agreement as to how sequences should be defined and analysed. Our review aims to outline suitable methods for testing these hypotheses, and to describe the major limitations to our current and near-future knowledge on questions of acoustic sequences. This review and prospectus is the result of a collaborative effort between 43 scientists from the fields of animal behaviour, ecology and evolution, signal processing, machine learning, quantitative linguistics, and information theory, who gathered for a 2013 workshop entitled, 'Analysing vocal sequences in animals'. Our goal is to present not just a review of the state of the art, but to propose a methodological framework that summarises what we suggest are the best practices for research in this field, across taxa and across disciplines. We also provide a tutorial-style introduction to some of the most promising algorithmic approaches for analysing sequences. We divide our review into three sections: identifying the distinct units of an acoustic sequence, describing the different ways that information can be contained within a sequence, and analysing the structure of that sequence. Each of these sections is further subdivided to address the key questions and approaches in that area. We propose a uniform, systematic, and comprehensive approach to studying sequences, with the goal of clarifying research terms used in different fields, and facilitating collaboration and comparative studies. Allowing greater interdisciplinary collaboration will facilitate the investigation of many important questions in the evolution of communication and sociality.

Concurrent Bursty Behavior of Social Sensors in Sporting Events.

The advent of social media expands our ability to transmit information and connect with others instantly, which enables us to behave as "social sensors." Here, we studied concurrent bursty behavior of Twitter users during major sporting events to determine their function as social sensors. We show that the degree of concurrent bursts in tweets (posts) and retweets (re-posts) works as a strong indicator of winning or losing a game. More specifically, our simple tweet analysis of Japanese professional baseball games in 2013 revealed that social sensors can immediately react to positive and negative events through bursts of tweets, but that positive events are more likely to induce a subsequent burst of retweets. We confirm that these findings also hold true for tweets related to Major League Baseball games in 2015. Furthermore, we demonstrate active interactions among social sensors by constructing retweet networks during a baseball game. The resulting networks commonly exhibited user clusters depending on the baseball team, with a scale-free connectedness that is indicative of a substantial difference in user popularity as an information source. While previous studies have mainly focused on bursts of tweets as a simple indicator of a real-world event, the temporal correlation between tweets and retweets implies unique aspects of social sensors, offering new insights into human behavior in a highly connected world.

A rhythm landscape approach to the developmental dynamics of birdsong.

Unlike simple biological rhythms, the rhythm of the oscine bird song is a learned time series of diverse sounds that change dynamically during vocal ontogeny. How to quantify rhythm development is one of the most important challenges in behavioural biology. Here, we propose a simple method, called 'rhythm landscape', to visualize and quantify how rhythm structure, which is measured as durational patterns of sounds and silences, emerges and changes over development. Applying this method to the development of Bengalese finch songs, we show that the rhythm structure begins with a broadband rhythm that develops into diverse rhythms largely through branching from precursors. Furthermore, an information-theoretic measure, the Jensen-Shannon divergence, was used to characterize the crystallization process of birdsong rhythm, which started with a high rate of rhythm change and progressed to a stage of slow refinement. This simple method provides a useful description of rhythm development, thereby helping to reveal key temporal constraints on complex biological rhythms.

Tracking Time Evolution of Collective Attention Clusters in Twitter: Time Evolving Nonnegative Matrix Factorisation.

Micro-blogging services, such as Twitter, offer opportunities to analyse user behaviour. Discovering and distinguishing behavioural patterns in micro-blogging services is valuable. However, it is difficult and challenging to distinguish users, and to track the temporal development of collective attention within distinct user groups in Twitter. In this paper, we formulate this problem as tracking matrices decomposed by Nonnegative Matrix Factorisation for time-sequential matrix data, and propose a novel extension of Nonnegative Matrix Factorisation, which we refer to as Time Evolving Nonnegative Matrix Factorisation (TENMF). In our method, we describe users and words posted in some time interval by a matrix, and use several matrices as time-sequential data. Subsequently, we apply Time Evolving Nonnegative Matrix Factorisation to these time-sequential matrices. TENMF can decompose time-sequential matrices, and can track the connection among decomposed matrices, whereas previous NMF decomposes a matrix into two lower dimension matrices arbitrarily, which might lose the time-sequential connection. Our proposed method has an adequately good performance on artificial data. Moreover, we present several results and insights from experiments using real data from Twitter.

Quantifying collective attention from tweet stream.

Online social media are increasingly facilitating our social interactions, thereby making available a massive "digital fossil" of human behavior. Discovering and quantifying distinct patterns using these data is important for studying social behavior, although the rapid time-variant nature and large volumes of these data make this task difficult and challenging. In this study, we focused on the emergence of "collective attention" on Twitter, a popular social networking service. We propose a simple method for detecting and measuring the collective attention evoked by various types of events. This method exploits the fact that tweeting activity exhibits a burst-like increase and an irregular oscillation when a particular real-world event occurs; otherwise, it follows regular circadian rhythms. The difference between regular and irregular states in the tweet stream was measured using the Jensen-Shannon divergence, which corresponds to the intensity of collective attention. We then associated irregular incidents with their corresponding events that attracted the attention and elicited responses from large numbers of people, based on the popularity and the enhancement of key terms in posted messages or "tweets." Next, we demonstrate the effectiveness of this method using a large dataset that contained approximately 490 million Japanese tweets by over 400,000 users, in which we identified 60 cases of collective attentions, including one related to the Tohoku-oki earthquake. "Retweet" networks were also investigated to understand collective attention in terms of social interactions. This simple method provides a retrospective summary of collective attention, thereby contributing to the fundamental understanding of social behavior in the digital era.

Stepwise acquisition of vocal combinatorial capacity in songbirds and human infants.

Human language, as well as birdsong, relies on the ability to arrange vocal elements in new sequences. However, little is known about the ontogenetic origin of this capacity. Here we track the development of vocal combinatorial capacity in three species of vocal learners, combining an experimental approach in zebra finches (Taeniopygia guttata) with an analysis of natural development of vocal transitions in Bengalese finches (Lonchura striata domestica) and pre-lingual human infants. We find a common, stepwise pattern of acquiring vocal transitions across species. In our first study, juvenile zebra finches were trained to perform one song and then the training target was altered, prompting the birds to swap syllable order, or insert a new syllable into a string. All birds solved these permutation tasks in a series of steps, gradually approximating the target sequence by acquiring new pairwise syllable transitions, sometimes too slowly to accomplish the task fully. Similarly, in the more complex songs of Bengalese finches, branching points and bidirectional transitions in song syntax were acquired in a stepwise fashion, starting from a more restrictive set of vocal transitions. The babbling of pre-lingual human infants showed a similar pattern: instead of a single developmental shift from reduplicated to variegated babbling (that is, from repetitive to diverse sequences), we observed multiple shifts, where each new syllable type slowly acquired a diversity of pairwise transitions, asynchronously over development. Collectively, these results point to a common generative process that is conserved across species, suggesting that the long-noted gap between perceptual versus motor combinatorial capabilities in human infants may arise partly from the challenges in constructing new pairwise vocal transitions.

Structural design principles of complex bird songs: a network-based approach.

Bird songs are acoustic communication signals primarily used in male-male aggression and in male-female attraction. These are often monotonous patterns composed of a few phrases, yet some birds have extremely complex songs with a large phrase repertoire, organized in non-random fashion with discernible patterns. Since structure is typically associated with function, the structures of complex bird songs provide important clues to the evolution of animal communication systems. Here we propose an efficient network-based approach to explore structural design principles of complex bird songs, in which the song networks--transition relationships among different phrases and the related structural measures--are employed. We demonstrate how this approach works with an example using California Thrasher songs, which are sequences of highly varied phrases delivered in succession over several minutes. These songs display two distinct features: a large phrase repertoire with a 'small-world' architecture, in which subsets of phrases are highly grouped and linked with a short average path length; and a balanced transition diversity amongst phrases, in which deterministic and non-deterministic transition patterns are moderately mixed. We explore the robustness of this approach with variations in sample size and the amount of noise. Our approach enables a more quantitative study of global and local structural properties of complex bird songs than has been possible to date.

Evolution of birdsong syntax by interjection communication.

Animals use diverse forms of communication, from sound signals to body postures. Recent ethological studies have reported a unique syntactic communication of a songbird, the Bengalese finch (Lonchura striata var. domestica). Male Bengalese finches sing complex courtship songs, which can be reconstructed by finite automata, and female Bengalese finches prefer complex songs, as opposed to monotonous or random ones. These facts suggest that the song syntaxes of male birds may have evolved as a result of sexual selection by female birds. Inspired by this hypothesis, we developed a communication model that is a system coupling different types of automaton, one for song production by males and another for song evaluation by females. We applied this model to study the evolution of syntactic animal communication in terms of the self-organization of coevolving automata. Three types of courting strategies as well as a relationship between the song syntax and female preference emerged. We argue that despite the simple communication involved, the complexity and diversity of song syntaxes can evolve via diverse female preferences.