Ewa M. Golonka's research while affiliated with Loyola University Maryland and other places

Publications (18)

Book
This book presents a broad, multidisciplinary review of the factors that have been shown to or might influence sharing information on social media, regardless of its veracity. Drawing on literature from psychology, sociology, political science, communication, and information studies, the book provides a high-level framework of information sharing....
Chapter
The act of sharing information online depends on the actor’s ability to share—that is, having access to social media platforms, being willing to use social media, and being familiar with relevant technology. Several social media affordances also play a role in whether people share online content. These affordances are both sociotechnical (i.e., the...
Chapter
Messages originate from a variety of sources. Social media users may create content, observe a message or narrative, or seek one out. What people view is influenced by what they search for and what is being shared already in their social networks.
Chapter
This book contributes to the study of the propagation of information on social media by reviewing a broad multidisciplinary literature, leveraging theory and findings from information sciences, psychology, sociology, communication, political science, and more. We created a framework of information sharing on social media that also included findings...
Chapter
Genuine actors will react to the message they read and the messenger they encounter. We categorized these reactions into those related to affect and engagement (e.g., high arousal-specific emotions such as surprise or disgust) and those related to cognitive factors that influence belief, including factors that prompt individuals to engage in heuris...
Chapter
This chapter tackled three major aspects of the social context: culture, narratives, and language; social comparison of beliefs and norms; and the structure and composition of one’s social network. These factors may have an impact not only on sharing behavior directly, but also on motivations and reactions to narratives and information. Culture, wh...
Chapter
The literature identifies multiple motivations underlying individuals’ drive to share information on social media. We categorized these motivations using the psychological concept of needs that all humans have (i.e., need for impression management and enhancement, need for self-consistency and social identity, need for accuracy, and need for affili...
Chapter
Non-genuine actors, including social bots and sockpuppets, are automated or manipulated to post information and sentiment to various social media platforms. Though not all social bots and sockpuppets are nefarious, there is evidence that some of these non-genuine accounts—especially on Facebook and Twitter—are maliciously managed by hackers or stat...
Conference Paper
Full-text available
Learning a third language (L3) that is closely-related to a second language (L2) is an efficient way to leverage existing linguistic knowledge. One particular US population that is commonly taught a closely-related L3 is native or advanced L2 Spanish speakers learning Portuguese (Carvalho, Freire, & da Silva, 2010). Recent research has focused on f...
Conference Paper
Structural topic modeling (STM) is a recently introduced technique to model how the content of a collection of documents changes as a function of variables such as author identity or time of writing. We present two proof-of-concept applications of STM using Russian social media data. In our first study, we model how topics change over time, showing...
Conference Paper
Sockpuppets are online identities controlled by a user or group of users to manipulate the dissemination of information in digital environments. This manipulation can distort computational assessments of public opinion in social media. Using Russian-language Twitter data from the Ukrainian crisis in 2014, we present a proof-of-concept model employi...
Article
Despite years of research on vocabulary learning and teaching, relatively little is known about strategies for effective mastery of vocabulary in less commonly taught languages. The current study focuses on English native speakers studying Modern Standard Arabic to identify effective ways to present and learn new vocabulary using tasks varying in t...
Article
Full-text available
In previous studies of homework in core academic subjects, positive student attitudes toward homework were linked to higher achievement, whereas time spent on homework showed an inconsistent relationship with achievement. This study examined the generalizability of these findings to foreign language learning by analyzing 2,342 adult students' attit...
Article
This study examines the importance of interaction for second language (L2) acquisition by analyzing outcomes from two types of out-of-class activities. The study compared: (a) interactive homework, completed via text chat, and (b) individual homework, completed via independent writing. In a between-subjects design, participants in two intermediate-...
Article
Full-text available
This review summarizes evidence for the effectiveness of technology use in foreign language (FL) learning and teaching, with a focus on empirical studies that compare the use of newer technologies with more traditional methods or materials. The review of over 350 studies (including classroom-based technologies, individual study tools, network-based...

Citations

... We have yet to see the evaluation of the effectiveness of adaptive or other language learning technologies for Indigenous languages. Given this information and a need for effective educational resources to support Indigenous language learning [34], we created a game that aims to support the development of phonological awareness in Plains Cree (nehiyawewin) with the hope that it would be the first step in a series that supports improved listening and speaking skills among learners. ...
... Furthermore, these topics also motivate theory development by highlighting a new class of problems in need of further explanation: only a small fraction of online content draws sufficient attention and interest to be shared on social media. Understanding the psychology that underpins the dynamics of social media sharing is an important emerging subfield in psychology [21,67,112] (in addition to other areas such as computer science [76], political science [113], communication [114], and public health [115], among others [116]), driven in large part by concerns about misinformation. Tackling these questions ...
... Such filtering may happen at two levels-first at a thematic level, to exclude comments that do not fit the researcher's criteria, and second, to exclude those that prima facie appear authentic but may be fabricated. Recent studies (Crabb et al., 2015;Freelon et al., 2020;Graham et al., 2020) have highlighted the concern of highly organized online activists who can influence and contaminate data with the use of bots (automated content creation tools), spam (mass communication messaging), and "sockpuppets" (a fake account designed to distort and manipulate public opinion). Despite acknowledging the challenges in using social media data, few studies have explored this process and how it may be applied effectively in practice (Graham et al., 2020). ...
... For example, Ragini et al. (2018) used a set of keywords that refer to danger, such as "trapped, stranded, help, save, rescue, struck, caught" to extract relevant information from disaster-related tweets. Mishler et al. (2015) used the Structural Topic Model (STM), a variant of LDA, to capture temporal changes in the Ukrainian crisis. Kireyev et al. (2009) used basic LDA on Twitter data from two earthquakes in America and Indonesia to uncover the most prominent topics during these two natural disasters. ...
... • Fits with previous finding that not all cognates are categorically perceived as cognates 12  The use of IPA makes the metric flexible, allowing for comparisons: ...
... Most of CALL research is not presented through a materials use perspective; however, there are multiple examples that have explored how learners use a specific digital material in a classroom setting, such as web-based tool for vocabulary learning (e.g., Juffs and Friedline 2014), corpus tools (e.g., Park 2012; Park and Kinginger 2010), videoconferencing (e.g., Hampel and Stickler 2012), writing iPad applications (e.g., Dagenais et al. 2017), recording videos (e.g. Toohey et al. 2015) and chat exchanges (e.g., Jenks 2014; Tare et al. 2014), among others. ...
... In L2 Arabic, Golonka et al. (2015) found similar patterns in vocabulary gains in line with ILH predictions. Mohamed (2016) tested ILH on intermediate learners of Arabic through three learning tasks, ranging from the low cognitive load (reading comprehension with glosses) to medium load (fill-in-the-gap) and high load (sentence writing). ...
... Yet, as argued by Trautwein and Köller (2003), total time and active time are often conflated when measuring homework time. In addition, "spending a lot of time on homework might signify a rather inefficient, unmotivated homework style" (Trautwein, 2007, p. 385) or due to learning difficulties (Chang et al., 2014). Drawn from the data from 1,275 graders in Switzerland, Trautwein et al. (2009) reported that homework time negatively predicted student achievement. ...
... Most computer-aided language learning systems [15,18], e.g., foreign language learning [10] and teaching hearing-impaired patients [14,30], include a computer-assisted pronunciation tool (CAPT) [1,31]. A typical CAPT records a learner's utterance, detects and diagnoses mispronunciations in it, and suggests a way for correcting them [1]. ...