Introductory Chapter: Data Streams and Online Learning in Social Media

People use social media (SM) to describe and discuss different situations in which they are involved, such as crises. It is therefore useful to exploit SM content to support crisis management, especially by revealing useful and unknown information about real-time crises. Therefore, we propose a new active online multi-prototype classifier called AOMPC. It identifies relevant data related to a crisis. AOMPC is an online learning algorithm that runs on data streams and contains active learning algorithms for actively querying the label of obscure unnamed data. The number of queries is controlled by a consistent budget strategy. In general, AOMPC allows for somewhat labeled data streams. AOMPC evaluated using two types of data: (1) synthetic data and (2) SM data from Twitter related to two crises, the Colorado floods and the Australian pushfires. To provide a complete estimate, a complete set of known measurements was used to examine the quality of the results. Furthermore, a sensitivity analysis was conducted to show the effect of the parameters of AOMPC on the accuracy of the results. AOMPC's comparative study was conducted against other available online learning methods. Tests to handle emerging, somewhat labeled data streams showed AOMPC's excellent behavior.

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Introduction to the Digital Street

10.1093/oso/9780199381265.003.0001 ◽

2018 ◽

Author(s):

Jeffrey Lane

Keyword(s):

Social Media ◽

The Internet ◽

Outreach Worker ◽

Digital Form ◽

Street Life ◽

Black And Latino

The first chapter introduces the concept of the digital street. The author argues that a digital form of street life plays out alongside the neighborhood on social media. The author discusses how the traditional boundaries of street life and the street code in particular have shifted as neighborhood space extends online. Black and Latino teenagers now experience their neighborhood differently from previous generations. The author explains the fieldwork this book is based upon. The author describes meeting “Pastor” and becoming an outreach worker in his peace ministry and then taking on additional roles online and offline with teenagers and concerned adults. This introductory chapter also gives background on access to smartphones and the Internet. A brief description of the contents of each chapter and the order of the chapters is provided.

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“Teachers Act Like We’re Robots”: TikTok as a Window Into Youth Experiences of Online Learning During COVID-19

AERA Open ◽

10.1177/2332858421995537 ◽

2021 ◽

Vol 7 ◽

pp. 233285842199553

Author(s):

Ioana Literat

Keyword(s):

Social Media ◽

Online Learning ◽

Thematic Analysis ◽

Large Scale ◽

Home School ◽

Educational Support ◽

Social Lives ◽

Online Coursework ◽

Youth Experiences ◽

Educational Futures

Social media, and especially popular youth-focused platforms like TikTok, can offer a valuable window into youth experiences, including their perceptions of online learning. Building on a large-scale thematic analysis of 1,930 TikTok videos posted in March-June 2020, this study examines how young people shared their experiences of online learning during the COVID-19 pandemic. Findings indicate that youth portrayed online coursework as overwhelming and relentless against the traumatic background of the pandemic. They sought support, empathy, and authenticity from teachers, and both received and provided emotional and educational support to peers on the platform. Students’ home contexts emerged as particularly salient, making visible the intersections between young people’s home, school and social lives. By facilitating a grounded, bottom-up understanding of students’ experiences and perceptions—shared in their preferred spaces and modes of expression—this research stresses the need to attend to youth perspectives to craft more equitable and empowering educational futures.

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Social media activity: its impact on career-related perceptions

Development in Learning Organizations An International Journal ◽

10.1108/dlo-09-2021-0162 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Kimberly W. O'Connor ◽

Kimberly S. McDonald ◽

Brandon T. McDaniel ◽

Gordon B. Schmidt

Keyword(s):

Social Media ◽

Online Learning ◽

Career Satisfaction ◽

Media Use ◽

Positive Impact ◽

Amazon Mechanical Turk ◽

Social Media Use ◽

Content Type ◽

The Impact ◽

Career Benefits

Purpose The purpose of this exploratory study is to examine individual perceptions about the impact that social media use has on career satisfaction and perceived career benefits. We examined whether informal online learning through “typical” types of social media behaviors (e.g. liking a post or messaging another user) and “networking” types of social media behaviors (e.g. endorsing another user, writing recommendations, going “live,” or looking for a job) impacted career-related perceptions. Design/methodology/approach In this study, we analyzed Amazon Mechanical Turk survey data gathered from adult participants (n = 475). We focused our inquiry specifically on two social media sites, Facebook and LinkedIn. We asked participants about their social media use and behaviors, as well as their perceptions of career satisfaction and career benefits related to social media. Findings We found that both typical and networking types of social media behaviors positively predicted the “knowing whom” career competency (defined as career relevant networks and contacts that individuals use to develop their careers) and career satisfaction. Only networking behaviors were positively associated with perceived career benefits of social media use. We further found that LinkedIn users’ career satisfaction was lower compared to non-LinkedIn users. Originality/value This study adds to the small, but growing body of career research focusing on social capital and social media. Our results suggest that informal online learning via social media may have a positive impact on employees’ career-related perceptions.

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