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The steady increase of data on human behavior collected online holds significant research potential for social scientists. The purpose of this paper is to add a systematic discussion of different online services, their data generating processes, the offline phenomena connected to these data, and by demonstrating, in a proof of concept, a new approach for the detection of extraordinary offline phenomena by the analysis of online data.

To detect traces of extraordinary offline phenomena in online data, the paper determines the normal state of the respective communication environment by measuring the regular dynamics of specific variables in data documenting user behavior online. In its proof of concept, the paper does so by concentrating on the diversity of hashtags used on Twitter during a given time span. The paper then uses the seasonal trend decomposition procedure based on loess (STL) to determine large deviations between the state of the system as forecasted by the model and the empirical data. The paper takes these deviations as indicators for extraordinary events, which led users to deviate from their regular usage patterns.

The paper shows in the proof of concept that this method is able to detect deviations in the data and that these deviations are clearly linked to changes in user behavior triggered by offline events.

The paper adds to the literature on the link between online data and offline phenomena. The paper proposes a new theoretical approach to the empirical analysis of online data as indicators of offline phenomena. The paper will be of interest to social scientists and computer scientists working in the field.

The purpose of this paper is to report effect of rotation of micropolar thermoelastic solid with microtemperatures heated by laser pulses. The problem was solved analytically to obtain the expressions of the physical quantities.

The analytical method used was the normal mode.

Numerical results for the physical quantities were presented graphically and the results were analyzed. The comparisons were established in variant cases of the effects used and then shown graphically.

In the present work, the authors shall discuss the effect of rotation and temperature-dependent properties with the laser pulses in the micropolar thermoelastic medium with microtemperatures. This problem is very important in more empirical branches such as the human body and earthquake engineering.

Using the Jefimenko generalization of the Biot‐Savart law and the Laplace transform we analyse the electromagnetic radiation of a vertical dipole antenna fed with a pulsed current. We get the magnetic field from the vector potential directly while the electric field is obtained through Maxwell’s equations. We write explicitly the expressions of the electromagnetic field for an exponentially decaying pulse and for a truncated harmonic pulse in vacuum and in a dispersive dielectric of the ionosphere type.

The COVID-19 pandemic triggered an increase in online traffic, with many assuming that this technology would facilitate coping through active social connections. This study aims to interrogate the nature of this traffic-engagement relationship by distinguishing between passive (e.g. browsing) and active (e.g. reacting, commenting and sharing) engagement, and examining behavioral shifts across platforms.

Three field studies assessed changes in social media engagement during the COVID-19 pandemic. These studies included social media engagement with the most followed accounts (Twitter), discussion board commenting (Reddit) and news content sharing (Facebook).

Even though people spent more time online during the pandemic, the current research finds people were actively engaging less. Users were reacting less to popular social media accounts, commenting less on discussion boards and even sharing less news content.

While the current work provides a systematic observation of engagement during a global crisis, it does not claim causality based on its correlational nature. Future research should test potential mechanisms (e.g. anxiety, threat and privacy) to draw causal inference and identify possible interventions.

The pandemic shed light on a complex systemic issue: the misunderstanding and oversimplification of how online platforms facilitate social cohesion. It encourages thoughtful consideration of online social dynamics, emphasizing that not all engagement is equal and that the benefits of connection may not always be realized as expected.

This research provides a postmortem on the traffic-engagement relationship, highlighting that increased online presence does not necessarily translate to active social connection, which might help explain the rise in mental health issues that emerged from the pandemic.

The purpose of this paper is to verify the relationship between the features of social media and knowledge sharing, and to examine how ambient awareness mediates this relationship.

An experiment is designed to stimulate the knowledge work in a famous Chinese business college and 156 valid samples were obtained. AMOS was used in this paper to examine the theoretical model.

There is a correlation among features of social media, ambient awareness and knowledge sharing. Surprisingly, network translucence, which indicates individuals’ meta-knowledge of others’ connections, has no influence on knowledge sharing. Although this is inconsistent with conjecture of the existing literature, it can be well explained by the phenomenon in real life, such as privacy setting in social media.

For employees who use social media to promote knowledge sharing within organizations, this study reminds them of the importance of ambient awareness. For managers, this study can give them some suggestions to make employees take full advantage of social media to achieve optimal benefits of knowledge sharing, thus improving organizational performance and innovation. For social media designers, they can make social media more useful in knowledge work by improving its specific features.

This paper proposes that ambient awareness is the mediator of the effect path between communication and knowledge sharing. And the status perception of coworkers’ exchanging information is closely related to knowledge sharing.

Social media provide an impressive amount of data about users and their interactions, thereby offering computer and social scientists, economists, and statisticians – among others – new opportunities for research. Arguably, one of the most interesting lines of work is that of predicting future events and developments from social media data. However, current work is fragmented and lacks of widely accepted evaluation approaches. Moreover, since the first techniques emerged rather recently, little is known about their overall potential, limitations and general applicability to different domains. Therefore, better understanding the predictive power and limitations of social media is of utmost importance.

Different types of forecasting models and their adaptation to the special circumstances of social media are analyzed and the most representative research conducted up to date is surveyed. Presentations of current research on techniques, methods, and empirical studies aimed at the prediction of future or current events from social media data are provided.

A taxonomy of prediction models is introduced, along with their relative advantages and the particular scenarios where they have been applied to. The main areas of prediction that have attracted research so far are described, and the main contributions made by the papers in this special issue are summarized. Finally, it is argued that statistical models seem to be the most fruitful approach to apply to make predictions from social media data.

This special issue raises important questions to be addressed in the field of social media-based prediction and forecasting, fills some gaps in current research, and outlines future lines of work.

As a new corporation, the Delhi Metro (DMRC) began its relationship with the media, with a clean slate, and its care with the public relations function made for the establishment of a very cordial relationship with the print media and led to positive image building in the public eye. However, with the rise of electronic media and the proliferating channels' greater emphasis on sensationalism, the warmth in the relations began to subside. A major standoff with the electronic media and the experience of accidents during construction of Phase II of the project, led to the restructuring of the approach to media relations as well as internal restructuring of the PR department. The challenges and major incidents turned out to be hard-learnt lessons in managing the media in a dynamic environment.

The purpose of this study is, to compare laser-based additive manufacturing and subtractive methods. Laser-based manufacturing is a widely used, noncontact, advanced manufacturing technique, which can be applied to a very wide range of materials, with particular emphasis on metals. In this paper, the governing principles of both laser-based subtractive of metals (LB-SM) and laser-based powder bed fusion (LB-PBF) of metallic materials are discussed and evaluated in terms of performance and capabilities. Using the principles of both laser-based methods, some new potential hybrid additive manufacturing options are discussed.

Production characteristics, such as surface quality, dimensional accuracy, material range, mechanical properties and applications, are reviewed and discussed. The process parameters for both LB-PBF and LB-SM were identified, and different factors that caused defects in both processes are explored. Advantages, disadvantages and limitations are explained and analyzed to shed light on the process selection for both additive and subtractive processes.

The performance of subtractive and additive processes is highly related to the material properties, such as diffusivity, reflectivity, thermal conductivity as well as laser parameters. LB-PBF has more influential factors affecting the quality of produced parts and is a more complex process. Both LB-SM and LB-PBF are flexible manufacturing methods that can be applied to a wide range of materials; however, they both suffer from low energy efficiency and production rate. These may be useful when producing highly innovative parts detailed, hollow products, such as medical implants.

This paper reviews the literature for both LB-PBF and LB-SM; nevertheless, the main contributions of this paper are twofold. To the best of the authors’ knowledge, this paper is one of the first to discuss the effect of the production process (both additive and subtractive) on the quality of the produced components. Also, some options for the hybrid capability of both LB-PBF and LB-SM are suggested to produce complex components with the desired macro- and microscale features.