Issue Spatiality: A Conceptual Framework for the Role of Space in Public Discourses

Public spheres research has traditionally sidestepped questions of space by focusing on a priori delineated political territories, most prominently national public spheres. While this approach has always lacked nuance, it has become acutely insufficient nowadays, as digital communication technologies easily enable a host of heterogeneous actors to draw public attention to spaces and places at any scale, and communicatively connect places anywhere in the world. This conceptual article argues that communication scholars need to reconsider the spaces embedded in the content of public discourses. Drawing on the notion of issue publics, it understands the public definition of issues as inextricably linked to the places that are communicatively associated with them, causing issue spaces to emerge. The issue space is constructed through place-naming whenever public actors reference places in the context of issues. The article develops issue spatiality as an analytical framework to understand the role of place and space in public discourse. It discusses how issue spatiality enables a better understanding of the increasingly complex scales of public communication, and outlines several dimensions of issue spatiality. Drawing on communication infrastructure literature, it proposes socio-spatial inequalities of communicative resources as important predictors of issue spatiality, along with the habits of professional communicators, and local problem properties. Gazetteers and mapping techniques are introduced as methodological interventions required for the empirical use of issue spatiality

Tracing the Emergent Field of Digital Environmental and Climate Activism Research: A Mixed-Methods Systematic Literature Review

Following Fridays for Future’s transnational mobilization, research into digital environmental and climate activism has rapidly grown. We contribute to the solidification of this emerging field through a mixed-methods systematic literature review. We quantitatively analyze 138 peer-reviewed articles regarding their theories, methodologies, and empirical focus. To identify research trajectories and emerging fields of interest, we add an in-depth qualitative analysis of influential publications. Research interest has grown rapidly and shifted from various areas of environmental grievance towards climate change as the primary focus. The field is driven by theories of framing, connective action, and (in)visibility. It is methodologically diverse, but geographically biased towards the West. Popular approaches include ethnographic case studies and Twitter studies, while other platforms receive limited attention. We diagnose a need for more comparative and relational approaches going beyond individual cases, countries, and platforms

Community detection in civil society online networks: Theoretical guide and empirical assessment

Community detection is a fundamental challenge in the analysis of online networks. However, there is a lack of consensus regarding how to accomplish this task in a manner that acknowledges domain-specific, substantive social theory. We develop a typology of what social phenomena communities of hyperlinked actors may signify—topical similarities, ideological associations, strategic alliances, and potential user traffic—and offer recommendations for community detection grounded in these concepts. Testing procedures on a hyperlink network of the food safety movement, we demonstrate that the handling of tie directions and weights as well as algorithm choice influence which communities are ultimately detected in such a network

Who Are They and Where? Insights Into the Social and Spatial Dimensions of Imagined Audiences From a Mobile Diary Study of Twitter Users

Social media users hardly know who is reading their posts, but they form ideas about their readership. Researchers have coined the term imagined audience for the social groups that actors imagine seeing their public communication. However, social groups are not the only aspect that requires imagination: In the potentially borderless online environment, the geographical scope and locations of one’s audience are also unknown. Furthermore, research has demonstrated that imagined audiences vary between people and situations, but what explains these variations is unclear. In this article, we address these two gaps—the geographical scope and predictors of imagined audiences—using data from a mobile experience sampling method study of 105 active Twitter users from Berlin, Germany. Our results show that respondents mostly think of a geographically broad audience, which is spread out across the country or even globally. The imagined geographical scope and social groups depend on both the communicator and the usage situation. While the audience’s social composition especially depends on tweet content and respondents’ sociodemographic characteristics, the geographical scope is best explained by respondents’ biography and personal mobility, including their experience of living in other countries and local residential duration

Machine Translation Vs. Multilingual Dictionaries Assessing Two Strategies for the Topic Modeling of Multilingual Text Collections

The goal of this paper is to evaluate two methods for the topic modeling of multilingual document collections: (1) machine translation (MT), and (2) the coding of semantic concepts using a multilingual dictionary (MD) prior to topic modeling. We empirically assess the consequences of these approaches based on both a quantitative comparison of models and a qualitative validation of each method’s potentials and weaknesses. Our case study uses two text collections (of tweets and news articles) in three languages (English, Hebrew, Arabic), covering the ongoing local conflicts between Israeli authorities, settlers, and Palestinian Bedouins in the West Bank. We find that both methods produce a large share of equivalent topics, especially in the context of fairly homogenous news discourse, yet show limited but systematic differences when applied to highly heterogenous social media discourse. While the MD model delivers a more nuanced picture of conflict-related topics, it misses several more peripheral topics, especially those unrelated to the dictionary’s focus, which are picked up by the MT model. Our study is a first step toward instrument validation, indicating that both methods yield valid, comparable results, while method-specific differences remain

Tweeting in the Time of Coronavirus: How Social Media Use and Academic Research Evolve during Times of Global Uncertainty

Our international research team was in the midst of a comparative study about the day-to-day experience of Twitter users in Berlin and Jerusalem through a series of daily short surveys, when our Jerusalem data were becoming increasingly "compromised" by the growing public concern, and tightening government measures, around the spread of the Coronavirus in Israel. During the two waves of our 10-day survey of salient Twitter users in Jerusalem (March 9-March 19,N = 34; March 23-April 2, N = 25), Israel shifted from 50 confirmed Coronavirus cases to over 6,800 and from relative routine to almost full stay-at-home orders. This essay presents two intersecting narratives. First, we consider the methodological challenges of adapting ongoing academic survey studies to changing conditions. We then offer a mixed-methods analysis of the experiences of our Twitter users and how they saw the Coronavirus crisis shaping their use of Twitter. The essay thus offers a unique methodological and empirical vantage point on how social media use-and academic research-evolve during times of global uncertainty

Induktive Kategorienbildung in der Inhaltsanalyse: Kombination automatischer und manueller Verfahren

Kernstück jeder Inhaltsanalyse ist ein Kategoriensystem, das häufig induktiv-qualitativ an einer kleinen Stichprobe von Texten entwickelt wird. Methoden des Text Mining ermöglichen es heute, eine nahezu unbegrenzte Anzahl an Texten effizient, schnell und nachvollziehbar zu explorieren. In diesem Beitrag wird ein Verfahren vorgeschlagen, bei dem solche Methoden eingesetzt werden, um induktiv aus einem umfangreichen Textkorpus Kategorien für eine Inhaltsanalyse zu bilden. Diese Methoden werden mit einer qualitativen, manuellen Inhaltsanalyse kombiniert. Die Kombination verschiedener Verfahren besteht darin, dass zunächst mittels Text Mining thematische Oberkategorien aus einem vorliegenden Textkorpus extrahiert, anschließend manuell validiert und in einer qualitativen Inhaltsanalyse um Unterkategorien erweitert wurden. Das Vorgehen wird beispielhaft an einem Codebuch erläutert, welches im Rahmen der Auswertung des "Bürgerdialogs" der Bundesregierung "Gut leben in Deutschland" zum Thema Lebensqualität entwickelt und angewendet wurde

Changes in parental smoking during pregnancy and risks of adverse birth outcomes and childhood overweight in Europe and North America : An individual participant data meta-analysis of 229,000 singleton births

Author summaryWhy was this study done? Maternal smoking during pregnancy is an important risk factor for various birth complications and childhood overweight. It is not clear whether this increased risk is also present if mothers smoke during the first trimester only or reduce the number of cigarettes during pregnancy. The associations of paternal smoking with birth and childhood outcomes also remain unknown. What did the researchers do and find? We conducted an individual participant data meta-analysis using data from 229,158 families from 28 pregnancy and birth cohorts from Europe and North America to assess the associations of parental smoking during pregnancy, specifically of quitting or reducing smoking and maternal and paternal smoking combined, with preterm birth, small size for gestational age, and childhood overweight. We observed that smoking in the first trimester only did not increase the risk of preterm birth and small size for gestational age but was associated with a higher risk of childhood overweight, as compared to nonsmoking. Reducing the number of cigarettes during pregnancy, without quitting, was still associated with higher risks of these adverse outcomes. Paternal smoking seems to be associated, independently of maternal smoking, with the risks of childhood overweight. What do these findings mean? Population strategies should focus on parental smoking prevention before or at the start of, rather than during, pregnancy. Future studies are needed to assess the specific associations of smoking in the preconception and childhood periods with offspring outcomes. Background Fetal smoke exposure is a common and key avoidable risk factor for birth complications and seems to influence later risk of overweight. It is unclear whether this increased risk is also present if mothers smoke during the first trimester only or reduce the number of cigarettes during pregnancy, or when only fathers smoke. We aimed to assess the associations of parental smoking during pregnancy, specifically of quitting or reducing smoking and maternal and paternal smoking combined, with preterm birth, small size for gestational age, and childhood overweight. Methods and findings We performed an individual participant data meta-analysis among 229,158 families from 28 pregnancy/birth cohorts from Europe and North America. All 28 cohorts had information on maternal smoking, and 16 also had information on paternal smoking. In total, 22 cohorts were population-based, with birth years ranging from 1991 to 2015. The mothers' median age was 30.0 years, and most mothers were medium or highly educated. We used multilevel binary logistic regression models adjusted for maternal and paternal sociodemographic and lifestyle-related characteristics. Compared with nonsmoking mothers, maternal first trimester smoking only was not associated with adverse birth outcomes but was associated with a higher risk of childhood overweight (odds ratio [OR] 1.17 [95% CI 1.02-1.35],Pvalue = 0.030). Children from mothers who continued smoking during pregnancy had higher risks of preterm birth (OR 1.08 [95% CI 1.02-1.15],Pvalue = 0.012), small size for gestational age (OR 2.15 [95% CI 2.07-2.23],Pvalue <0.001), and childhood overweight (OR 1.42 [95% CI 1.35-1.48],Pvalue <0.001). Mothers who reduced the number of cigarettes between the first and third trimester, without quitting, still had a higher risk of small size for gestational age. However, the corresponding risk estimates were smaller than for women who continued the same amount of cigarettes throughout pregnancy (OR 1.89 [95% CI 1.52-2.34] instead of OR 2.20 [95% CI 2.02-2.42] when reducing from 5-9 to = 10 to 5-9 andPeer reviewe

Maternal body mass index, gestational weight gain, and the risk of overweight and obesity across childhood : An individual participant data meta-analysis

Background Maternal obesity and excessive gestational weight gain may have persistent effects on offspring fat development. However, it remains unclear whether these effects differ by severity of obesity, and whether these effects are restricted to the extremes of maternal body mass index (BMI) and gestational weight gain. We aimed to assess the separate and combined associations of maternal BMI and gestational weight gain with the risk of overweight/obesity throughout childhood, and their population impact. Methods and findings We conducted an individual participant data meta-analysis of data from 162,129 mothers and their children from 37 pregnancy and birth cohort studies from Europe, North America, and Australia. We assessed the individual and combined associations of maternal pre-pregnancy BMI and gestational weight gain, both in clinical categories and across their full ranges, with the risks of overweight/obesity in early (2.0-5.0 years), mid (5.0-10.0 years) and late childhood (10.0-18.0 years), using multilevel binary logistic regression models with a random intercept at cohort level adjusted for maternal sociodemographic and lifestylerelated characteristics. We observed that higher maternal pre-pregnancy BMI and gestational weight gain both in clinical categories and across their full ranges were associated with higher risks of childhood overweight/obesity, with the strongest effects in late childhood (odds ratios [ORs] for overweight/obesity in early, mid, and late childhood, respectively: OR 1.66 [95% CI: 1.56, 1.78], OR 1.91 [95% CI: 1.85, 1.98], and OR 2.28 [95% CI: 2.08, 2.50] for maternal overweight; OR 2.43 [95% CI: 2.24, 2.64], OR 3.12 [95% CI: 2.98, 3.27], and OR 4.47 [95% CI: 3.99, 5.23] for maternal obesity; and OR 1.39 [95% CI: 1.30, 1.49], OR 1.55 [95% CI: 1.49, 1.60], and OR 1.72 [95% CI: 1.56, 1.91] for excessive gestational weight gain). The proportions of childhood overweight/obesity prevalence attributable to maternal overweight, maternal obesity, and excessive gestational weight gain ranged from 10.2% to 21.6%. Relative to the effect of maternal BMI, excessive gestational weight gain only slightly increased the risk of childhood overweight/obesity within each clinical BMI category (p-values for interactions of maternal BMI with gestational weight gain: p = 0.038, p <0.001, and p = 0.637 in early, mid, and late childhood, respectively). Limitations of this study include the self-report of maternal BMI and gestational weight gain for some of the cohorts, and the potential of residual confounding. Also, as this study only included participants from Europe, North America, and Australia, results need to be interpreted with caution with respect to other populations. Conclusions In this study, higher maternal pre-pregnancy BMI and gestational weight gain were associated with an increased risk of childhood overweight/obesity, with the strongest effects at later ages. The additional effect of gestational weight gain in women who are overweight or obese before pregnancy is small. Given the large population impact, future intervention trials aiming to reduce the prevalence of childhood overweight and obesity should focus on maternal weight status before pregnancy, in addition to weight gain during pregnancy.Peer reviewe