How Do People with Late Bedtimes use Social Media?

Background: The use of social media before bedtime usually results in late bedtimes, which is a prevalent cause of insufficient sleep among the general population of most countries. However, it is still unclear how people with late bedtimes use social media, which is crucial for adopting targeted behavior interventions to prevent insufficient sleep. Methods: In this study, we randomly selected 100000 users from Sina Weibo and collected all their posting through web crawling. The posting time was proposed as a proxy to identify nights on which a user stays up late. A text classifier and topic model were developed to identify the emotional states and themes of their posts. We also analyzed their posting/reposting activity, time-use patterns, and geographical distribution. Results: Our analyses show that habitually late sleepers express fewer emotions and use social media more for entertainment and getting information. People who rarely stay up late feel worse when staying up late, and they use social media more for emotional expression. People with late bedtimes mainly live in developed areas and use smartphones more when staying up late. Conclusion: This study depicts the online behavior of people with late bedtimes, which helps understand them and thereby adopt appropriately targeted interventions to avoid insufficient sleep.

Social representations of Brazilian Truth Commission on news comments

The study investigated the social representations of the Brazilian Truth Commission from the news comments about its final report released in December 2014. Method: Comments (N = 322) were collected in the three major newspapers websites in Brazil: “Folha de São Paulo”, “O Globo” and “O Estado de São Paulo” during the 48 hours following the report’s publication. They were submitted to a lexical analysis on the software Radicalized discourses justifying the violations and narratives denying the existence of a dictatorship were observed. Discussion: Results were in line with social media theories about online behavior, but they do not corroborate previous research on the social representations of the military regime and Truth Commissions in South America. Received: 15 September 2021Accepted: 22 November 2021

Low Self-Control and Cybercrime Victimization: An Examination of Indirect Effects Through Risky Online Behavior

Research has established that individuals lower in self-control are at increased risk of offline criminal victimization due to their proclivity to engage in risky routine activities. While some studies have investigated whether a similar pattern is observed in the online context, additional inquiry into whether the link between low self-control and cybercrime victimization operates indirectly through risky online behavior is warranted given certain measurement and methodological limitations of prior research. Using original data collected on a sample of young adults, we find that the association between low self-control and a variety measure of cybercrime victimization operates entirely and indirectly through a variety measure of risky online behaviors. The implications of this finding for policy and programing are discussed.

Communicating across educational boundaries: accommodation patterns in adolescents’ online interactions

This paper studies linguistic accommodation patterns in a large corpus of private online conversations produced by Flemish secondary school students. We use Poisson models to examine whether the teenagers adjust their writing style depending on their interlocutor’s educational profile, while also taking into account the extent to which these adaptation patterns are influenced by the authors’ own educational background or by other aspects of their socio-demographic profiles. The corpus does reveal accommodation patterns, but the adjustments do not always mirror variation patterns related to educational profiles. While salient features like expressive markers seem to lead to pattern-matching, less salient features appear less prone to ‘adequate’ adjustment. Lack of familiarity with the online behavior of students from other educational tracks is a factor too, since online communication clearly proceeds primarily within ‘same-education’ networks. The focus on cross-educational communication is quite unique in this respect and highly relevant from a sociological perspective.

Verkko-oppimisympäristöjen kehittäminen tekoälyn avulla: Tulevaisuusvisio matematiikan opetuksen täydennyskoulutuksesta

Verkko-oppimisympäristöjen suosio kasvaa kiihtyvällä tahdilla maailman laajuisesti ja samaan aikaan tarve uusille lähestymistavoille verkko-oppimisen ja -opetuksen kehittämisessä ja tutkimuksessa on kasvanut. Vaikka lokitiedot mahdollistavat verkkokäyttäytymisen tutkimisen, on tätä mahdollisuutta hyödynnetty verkko-oppimisen ja -opetuksen tutkimuskontekstissa verrattain vähän. Tutkimuksessa hyödynnettiin lokitietoja verkkokurssin arvioinnissa ja kehittämisessä MOOC-ympäristössä. Tässä artikkelissa kuvataan oppimisprosessia lokitietojen avulla sekä pohditaan sitä, minkälaista ymmärrystä oppimisesta lokitiedot voivat tuottaa ja miten tällaisen tiedon voisi tulevaisuudessa valjastaa oppimisen tueksi. Tutkimusaineisto koostui matematiikan opettajien (N=58) täydennyskoulutusverkkokurssin lokitiedoista. Tutkimustulokset osoittavat, että syvällisemmät tai enemmän aikaa vaativat aktiviteetit keskeyttävät yhtenäisen opiskelun herkemmin kuin esimerkiksi videoluennot. Lyhytkestoiset videot ja nopeasti vastattavat kyselyt sen sijaan sitouttavat osallistujia yhtenäiseen opiskeluun. Vaikka suoristustavoissa on yksilöllisiä eroja, verkkokurssin kehittämistarvetta on mahdollista arvioida lokitietojen avulla. Esitämme artikkelissa vision siitä, kuinka tulevaisuudessa lokitiedot voisivat automaattisesti analysoitua, järjestelmä tunnistaisi oppimisprofiileja ja verkko-oppimisympäristö muokkautuisi automaattisesti tunnistettujen opiskelutaipumusten mukaan. Kun prosessiin yhdistetään tekoäly myös profilointialgoritmi kehittyisi automaattisesti käyttäjädatan kasvun myötä. In English Web-based learning enviroments have become increasingly popular world-wide. At the same time, the need for new approaches to both supporting and investigating teaching and learning have emerged. Although log information enables research of online behavior, this opportunity is not used to its full potential in the context of web-based teaching and learning. This research utilized log information in the assessment of a MOOC course and its development. This article describes the learning process with the help of log information. It also envisions what kind of understanding of the learning process log information can provide and how this understanding may be harnessed to support learning in the future. The data consisted of the log information of mathematic teachers (N=58) participating in an online continuing training course. The results show that in-depth time-consuming activities interrupt studying more easily than video lectures for example. Short videos and quick queries engage the participant in more coherent study. Although there are individual differences in the studying, less well-functioning teaching content and tasks can be recognized through log information. We present a vision of how log information can be automatically analyzed; the system would recognize learning profiles and the online environment would automatically modify itself according to the profile. When AI (artificial intelligence) is utilized the profiling algorithm would develop automatically as user data accumulates. Fulltext in Finnish.

Field Experiments on Social Media

Online behavioral data, such as digital traces from social media, have the potential to allow researchers an unprecedented new window into human behavior in ecologically valid everyday contexts. However, research using such data is often purely observational, which limits its usefulness for identifying causal relationships. Here we review recent innovations in experimental approaches to studying online behavior, with a particular focus on research related to misinformation and political psychology. In hybrid lab-field studies, exposure to social-media content can be randomized, and the impact on attitudes and beliefs can be measured using surveys, or exposure to treatments can be randomized within survey experiments, and their impact on subsequent online behavior can be observed. In field experiments conducted on social media, randomized treatments can be administered directly to users in the online environment (e.g., via social-tie invitations, private messages, or public posts) without revealing that they are part of an experiment, and the effects on subsequent online behavior can then be observed. The strengths and weaknesses of each approach are discussed, along with practical advice and central ethical constraints on such studies.

Online Information Seeking Behavior among Indonesian during the COVID-19 Pandemic

Background: The COVID-19 vaccination movement in Indonesia until mid-2021 has still not reached the expected number, which is less than 20% of the Indonesian population who receive the first dose of vaccine. Meanwhile, the government's target for accelerating herd immunity is to achieve immunization coverage of 70% by November 2021. Several issues have arisen regarding the public's reluctance to accept the COVID-19 vaccine, such as vaccine readiness, efficacy, conspiracy, halal issues, and the negative side of this vaccine. Aims: This study aims to assess the online behavior of the Indonesian community in seeking information related to the COVID-19 vaccine. Methods: Google trends was used as a data source to see the public interest in several issues including COVID, vaccines, and government policies. Analysis: The analysis was carried out descriptively. Results: The results of this study indicate the movement over time of society towards several terminologies in line with events or the implementation of policies in Indonesia. Conclusion: This research contributes to surveillance of the public's information needs on the COVID-19 issue to avoid misinformation.