The COVID-19 pandemic heightened burdens on caregivers, but also the visibility of caregiving inequalities. These grievances may activate a feminist identity which in turn leads to greater civic and political participation. During a pandemic, online forms of participation are particularly attractive as they require less effort than offline forms of participation and pose less health risks compared

This study examines the relationship between social media use and life satisfaction among older adults, with a focus on the moderating role of self-esteem. Cross-sectional data from the 2021 Korea Media Panel Survey were analyzed, focusing on responses from 192 older adults aged 65 and older who had experience using social media platforms. The findings reveal that among older adults with low self-esteem

This article poses a simple question: can AI lie? In response to this question, the article examines, as its point of inquiry, popular AI chatbots, such as, ChatGPT. In doing so, an examination of the psychoanalytic, philosophical, and technological significance of AI and its complexities are located in relation to the dynamics of truth, falsity, and deception. That is, by critically considering the

This article evaluates the quality of data collection in individual-level desktop web tracking used in the social sciences and shows that the existing approaches face sampling issues, validity issues due to the lack of content-level data and their disregard for the variety of devices and long-tail consumption patterns as well as transparency and privacy issues. To overcome some of these problems, the

Google Trends (GT) data are increasingly used in the social sciences and adjacent fields. However, previous research on the quality of GT data has raised concerns regarding their reliability. In the present study, we investigated whether reliability differs between low- and high-frequency search terms. In other words, we explored the existence of a reliability-frequency continuum in GT data. Our study

Instruction-tuned Large Language Models (LLMs) have recently emerged as a powerful new tool for text analysis. As these models are capable of zero-shot annotation based on instructions written in natural language, they obviate the need of large sets of training data—and thus bring potential paradigm-shifting implications for using text as data. While the models show substantial promise, their relative

Information technologies have transformed many aspects of social life, including how illegal goods are exchanged. Illegal online markets are now flourishing on various channels: the surface web (all websites accessible through a standard browser), the dark web (an encrypted internet network only accessible via anonymous browsers), and encrypted messaging applications installed on smartphones. These

This study undertook an analysis of network agenda setting during the 2020 U.S. Presidential campaign, focusing on the interactions between the campaigns and their respective supporters within the context of a polarized social media environment. By employing social network analysis techniques to examine issue agendas, the study revealed a relatively weak correlation between the agendas of the campaigns

This article presents the results of a comprehensive study examining the influence of bots on the dissemination of COVID-19 misinformation and negative vaccine stance on Twitter over a period of three years. The research employed a tripartite methodology: text classification, topic modeling, and network analysis to explore this phenomenon. Text classification, leveraging the Turku University FinBERT

Studying political opinions of citizens stands as a fundamental pursuit for both policymakers and researchers. While traditional surveys remain the primary method to investigate individual political opinions, the advent of social media data (SMD) offers novel prospects. However, the number of studies using SMD to extract individuals’ political opinions are limited and differ greatly in their methodological

This study aims to analyze news coverage on artificial intelligence (AI) issues and highlight the characteristics and differences in reporting based on media partisanship. By examining AI-related news in the South Korean media, this study reveals how conservative and progressive outlets frame the issue differently. The analysis found that conservative media coverage predominantly focuses on positive

Phubbing (phone snubbing) has become the norm in (im)polite society. A vast majority of US adults report using their phones during a recent social interaction. Using one’s phone in the presence of others has been shown to have a negative impact on relationships among co-workers, friends, family, and romantic partners. Recent research suggests viewing short-form videos (SFVs) (e.g., TikTok) is more

Modern Configurational Comparative Methods (CCMs), such as Qualitative Comparative Analysis (QCA) and Coincidence Analysis (CNA), have gained in popularity among social scientists over the last thirty years. A new CCM called Combinational Regularity Analysis (CORA) has recently joined this family of methods. In this article, we provide a software tutorial for the open-source package CORA, which implements

Recruitment materials for concurrent mixed-mode self-administered web and mail surveys must communicate information about multiple modes simultaneously. Providing the link to the web survey on the cover of the paper questionnaire or including a QR code to access the web survey may increase the visibility of the web mode and thus increase the proportion of people who participate via the web, but whether

Uncertainty in fertility intentions is a major obstacle to understanding contemporary trends in fertility decision-making and its outcomes. Quantifying this uncertainty by structural factors such as income, ethnicity, and housing conditions is recognized as insufficient. A recently proposed framework on subjective narratives has opened up a new way to gauge factors behind fertility decision-making

There is a close connection between video games and social life, and researchers are interested in whether and how video games shape aggression and prosocial behaviors. However, there are great inconsistencies across studies on this topic. These mixed results may be due in part to a focus on learning models that were relevant in research on traditional media like television but are less useful in research

The pervasive presence and influence of political bots have become the subject of extensive research in recent years. Studies have revealed that a significant percentage of active accounts are bots, contributing to the polarization of public sentiment online. This study employs an agent-based model in conducting computer simulations of complex social networks, to elucidate how bots, representing diverse

In this article, we analyze whether Twitter can be used to detect relative reports of issues at polling places. We use 20,322 tweets geolocated to U.S. states that match a series of keywords on the 2010, 2012, 2014, 2016, and 2018 general election days. We fine-tune BERTweet, a pre-trained language model, using a training set of 6,365 tweets labeled as issues or non-issues. We develop a model with

Academic publishing gender gap has been surprisingly under covered across all disciplines and over a longer timeframe. Our study fills this gap, by analyzing how the proportions of women authors change in academic publications over 20 years in all fields from 31,219 journals from 2001 to 2021. Our results indicate that the ratio of female to male authors keeps increasing steadily across disciplines

This study delves into Airbnb’s brand presence on TikTok by analyzing textual content in posts, and human audio in videos. This approach aims to decipher the brand narrative and gauge user engagement. In the dynamic realm of social media marketing, TikTok has emerged as a key platform in shaping brand perception. This research specifically concentrates on Airbnb’s content, distinguishing between official

Neighborhoods are important contexts in shaping interethnic group relationships and sites in which these may materialize through everyday routines in shared local spaces. In this paper, we approach neighborhoods as a small-scale set of spaces of encounter, defined as local public or semi-public spaces, where residents of different ethnic backgrounds may meet. Relying on the classical contact and group

Acknowledging the importance of focusing on media’s communication for studying linguistic sexism, we propose a new method to analyze a corpus of texts via a machine learning approach built around an original training-set. We seek to establish a framework of the current use of talking about women in newspapers that expands beyond merely the objective forms of discrimination by also measuring the degree

Social media has led to a redefinition of the journalist’s role. Specifically on Twitter, these professionals assume an influential position and their discourse is dominated by personal opinions. Taking into consideration that this platform has proven to be a breeding ground for polarization, digital harassment and hate speech, notably against women politicians, this research aims to analyze journalists’

Successful disinformation campaigns depend on the availability of fake social media profiles used for coordinated inauthentic behavior with networks of false accounts including bots, trolls, and sockpuppets. This study presents a scalable and unsupervised framework to identify visual elements in user profiles strategically exploited in nearly 60 influence operations, including camera angle, photo composition

The media attention to the personal sphere of famous and important individuals has become a key element of the gender narrative. In this setting, we aim at assessing gender gaps in the mediated personalization of a wide range of political office holders in Italy during the period 2017–2020 by means of a combination of NLP and statistical methods. The proposed analysis hinges on the definition of a

Algorithmic radicalization is the idea that algorithms used by social media platforms push people down digital “rabbit holes” by framing personal online activity. Algorithms control what people see and when they see it and learn from their past activities. As such, people gradually and subconsciously adopt the ideas presented to them by the rabbit hole down which they have been pushed. In this study

From the start of data collection for the 2020 US Census, official and celebrity users tweeted about the importance of everyone being counted in the Census and urged followers to complete the questionnaire (so-called social media campaign.) At the same time, social media posts expressing skepticism about the Census became increasingly common. This study distinguishes between different prototypical

Content analysis of political manifestos is necessary to understand the policies and proposed actions of a party. However, manually labeling political texts is time-consuming and labor-intensive. Transformer networks have become essential tools for automating this task. Nevertheless, these models require extensive datasets to achieve good performance. This can be a limitation in manifesto classification

The current study employs a construct from the criminological literature, thoughtfully reflective decision-making (TRDM), to understand cyber offenders’ decision-making and offer relevant insights to prevent online harassment. Using a sample of Iranian high school students ( N = 366), we employ OLS and SEM to test whether and how TRDM, perceived deterrence, and prior victimization influence the most

The smartphone increase in web surveys, coupled with technological developments, provides novel opportunities for measuring attitudes. For example, smartphones allow the collection of voice instead of text answers by using the built-in microphone. This may facilitate answering questions with open answer formats resulting in richer information and higher data quality. So far, there is only a little

Digital trace data are receiving increased attention as a potential way to capture human behavior. Nevertheless, this type of data is far from perfect and may not always provide better data compared to traditional social surveys. In this study we estimate measurement quality of survey and digital trace data on smartphone usage with a MultiTrait MultiMethod (MTMM) model. The experimental design included

Hashtag campaigns calling out sexual violence and rape myths offer a unique context for disclosing sexual victimization on social media. This study investigates the applicability of adaptive self-reflection as a potential self-effect from such public disclosures of unreported sexual victimization experiences by analyzing 92,583 tweets that invoked #WhyIDidntReport. A supervised machine learning classifier

In 2014, the EU introduced the lead candidate procedure to raise citizens’ awareness and interest in the European Parliament (EP) elections and, thereby, voter turnout. We study the use of personalization, centralized personalization (focusing on lead candidates), emotional personalization, and private personalization on Facebook by political parties across 12 countries during the 2014 and 2019 EP

Relatively little attention has been paid to the effects of nonparticipation on data quality in population-based studies that use accelerometers to measure physical activity. We examine these issues using data from the 2013 Longitudinal Internet Studies for the Social Sciences (LISS) panel and 2013–2014 National Health and Nutrition Examination Survey (NHANES) accelerometer studies, both of which collected

Incivility, that is, the breaking of social norms of conversation, is evidently prevalent in online political communication. While a growing literature provides evidence on the prevalence of incivility in different online venues, it is still unclear where and to what extent Internet users are exposed to incivility. This paper takes a comparative approach to assess the levels of incivility across contexts

Open-ended survey questions can enable researchers to gain insights beyond more commonly used closed-ended question formats by allowing respondents an opportunity to provide information with few constraints and in their own words. Open-ended web probes are also increasingly used to inform the design and evaluation of survey questions. However, open-ended questions are more susceptible to insufficient

Chatbots have a growing role to play in political discourse, including in political campaigns, voter mobilization ventures, and dissemination of political news, though chatbots in the political domain are relatively understudied. While testing the machine heuristics and political self-concepts frameworks, we carried out a 2 × 2 experiment where both perceived conversational partner (i.e., bot, human)

Over the last few years, Chile’s judicial system has witnessed a rise in criminal assumptions generated through social networks, under its hypotheses of funas, doxing, flagging or, in general, the exposure of the personal data of an individual, whether motivated by the performance of conduct of criminal relevance or simply of dubious morality or social appropriateness. Although these conducts originated

Many forms of online political incivility threaten democratic norms, contribute to polarization, and are often directed at women and racial minorities. Recent research shows that online political incivility may come from a minority of users that are just as hostile offline as they are online, meaning that individual differences in personality traits may be an important predictor of online political

This paper investigates how the acceptance of data-driven political campaigning depends on four different message characteristics. A vignette study was conducted in 25 countries with a total of 14,390 respondents who all evaluated multiple descriptions of political advertisements. Relying on multi-level models, we find that in particular the source and the issue of the message matters. Messages that

Simulation experiments have increased their influence on social science, creating a need for documentation tools and practices that facilitate replicability. Two crucial components common to many simulation experiments require particularly detailed documentation: the baseline parameterization, and the experimental designs. This paper explores the adaptability to these needs of a recent but already

Israeli-Jews and Palestinians cannot easily be exposed to contradicting information about “the other” in the intractable Israeli-Palestinian conflict because of the emotionally charged situation and prevailing ethnocentrism. Serious games like PeaceMaker are used as innovative interventions for peace education. Winning PeaceMaker indicates better conflict resolution skills and developing an informative

While survey data has long been the focus of quantitative social science analyses, observational and content data, although long-established, are gaining renewed attention; especially when this type of data is obtained by and for observing digital content and behavior. Today, digital technologies allow social scientists to track “everyday behavior” and to extract opinions from public discussions on

Online surveys are a widely used mode of data collection. However, as no interviewer is present, respondents face any difficulties they encounter alone, which may lead to measurement error and biased or (at worst) invalid conclusions. Detecting response difficulty is therefore vital. Previous research has predominantly focused on response times to detect general response difficulty. However, response

How does media coverage of electoral campaigns distinguish parties and candidates in emerging democracies? To answer, we present a multi-step procedure that we apply in South Africa. First, we develop a theoretically informed classification of election coverage as either “narrow” or “broad” from within the entire corpus of news coverage during an electoral campaign. Second, to deploy our classification

The October 2017 Las Vegas shooting was the deadliest shooting in modern American history, but little scholarship has examined the public uproar in its wake, particularly in digital networks. Drawing on a corpus of 100,000 public Tweets and 1,119,638 unique words written in reaction to the shooting, this article addresses this lacuna by investigating the topics of reactions and their linkages with

Large-scale data from private companies offer new opportunities to examine topics of scientific and social significance, such as racial inequality, partisan polarization, and activity-based segregation. However, because such data are often generated through automated processes, their accuracy and reliability for social science research remain unclear. The present study examines how quality issues in

Consuming conspiracy theories erodes trust in democratic institutions, while conspiracy beliefs demotivate democratic participation, posing a potential threat to democracy. The proliferation of social media, especially the emergence of numerous alternative platforms with minimal moderation, has greatly facilitated the dissemination and consumption of conspiracy theories. Nevertheless, there remains

This study examines the role of information sources in the ultra-Orthodox (Haredi) Jewish community’s coping with the coronavirus (COVID-19) pandemic in Israel by comparing their use of digital versus traditional information platforms. The study examined coping with COVID-19, considering explanatory variables such as Community Sense of Coherence (C-SOC), Internet usage, and other demographic variables

In this paper, we first frame the use of artificial intelligence (AI) systems in the public sector as a continuation and intensification of long-standing rationalization and bureaucratization processes. Drawing on Weber, we understand the core of these processes to be the replacement of traditions with instrumental rationality, that is, the most calculable and efficient way of achieving any given policy

Mobile Experience Sampling (MES) is a promising tool for understanding youth digital media use and its effects. Unfortunately, the method suffers from high levels of missing data. Depending on whether the data is randomly or non-randomly missing, it can have severe effects on the validity of findings. For this reason, we investigated predictors of non-response in an MES study on displacement effects

The use of individual-level browsing data, that is, the records of a person’s visits to online content through a desktop or mobile browser, is of increasing importance for social scientists. Browsing data have characteristics that raise many questions for statistical analysis, yet to date, little hands-on guidance on how to handle them exists. Reviewing extant research, and exploring data sets collected

Political campaigns are embracing the visual social media platform Instagram. One digital feature, the Story, has taken over feed sharing across social media. A Story is a sequence of images or videos uploaded to a profile that disappear after 24 hours. The Story is a novel feature relatively unexamined in political communications and marketing research. Specifically, it is unclear how Gubernatorial

Data is the new asset of the current digital revolution. It is heralded as the “new oil” that will transform the world and function as a magic tool for development policies, with great potential to solve global health dilemmas. However, deep societal inequalities give datafication the risk of escalating disparities through data policies instead of solving them. The pandemic unmasked the price to pay

The democratization of technology to re-create content and make that content publicly available has spurred a wave of user-generated content (UGC), which has produced remarkable social and economic benefits. However, under current copyright law, UGC creators face the dilemma of being deterred from creating UGC because of the risk of copyright infringement, copyright owners can rarely obtain remuneration

While digital technology use and skills have typically been measured with surveys, digital behavioral data that are passively collected from individuals’ digital devices have recently emerged as an alternative method of measuring technology usage patterns in a more unobtrusive and detailed way. In this paper, we evaluate how passively collected smartphone usage data compare to self-reported measures

Social networking sites (SNSs) have emerged as parallel societies, providing individuals with a platform to interact with peers and construct their desired self-identities. However, maintaining a positive image and safeguarding oneself from social judgment often necessitate self-censorship in self-identity expression. Drawing upon the privacy calculus theory, this study investigates how SNS users engage

This study examines how active participation, financial commitment, and passive participation in the leading social live-streaming service, Twitch.tv, relate to individuals’ psychological well-being. The three dimensions of social capital—structural, relational, and cognitive—as well as parasocial relationship are explored as mediators. Cross-sectional survey data from 396 respondents was analyzed

In 2017, Facebook’s news feed algorithm began weighting emoji reactions (e.g., love and angry) as five times more valuable than the like button. Such a change is theoretically intriguing because existing research largely suggests that women tend to use emojis more than men on social media. Within the context of political campaigns, prior work has revealed a host of other “gender gaps,” from documenting

As one of the most popular sources of information in the world, Wikipedia is edited by a large, global community of contributors. User-generated nature of this online encyclopedia ensures that the information reflects a wide range of topics. Hovewer, Wikipedia articles are created and edited independently in each language version. Therefore, some topics may be presented with varying degrees of completeness