Tie Strength vs. Network Overlap: Why Information from Lovers is More Valuable than from Close Friends on Social Network Sites?

Network structure is an important determinant of information value contained in individuals’ social networks. Researchers argue whether more value is contained in strongly connected cohesive networks or the weaker ones that are rich in structural holes. In the paper we differentiate between two measures of network structure - tie strength and network overlap – and explore their impact on the value of information that users derive from Social Network Sites. We analyze the data collected trough a survey administered to 121 Facebook users via a platform application. Our findings reveal that although users prefer information from their stronger ties on the network, high overlap in their networks decreases information value

An experimental analysis of bounded rationality: Applying insights from behavioral economics to information systems

The paradigm of bounded rationality considers the limited ability of individuals to make consistent and rational choices. Due to the scarcity of research on this phenomenon in information systems, we conducted an experimental study investigating decision-making regarding risk preferences and social preferences. Moreover, we explored the stability of these preferences under different conditions and uncovered the role of information retrieval in individual decision-making. We find that although individuals are generally risk-averse and egoistic, none of these preferences is stable under the conditions tested which provides indices of boundedly rational decision-making. Although the information retrieved by participants generally allows to infer their preferences, the increasing amount and complexity of this information again often results in boundedly rational behavior.bounded rationality, experimental design, information retrieval, stability of attitudes and behavior, cognitive tracing, behavioral economics, behavioral information systems

REDUCING INFORMATION OVERLOAD: DESIGN AND EVALUATION OF FILTERING & RANKING ALGORITHMS FOR SOCIAL NETWORKING SITES

Recognizing the detrimental impact of information overload on user participation, in this paper we design and evaluate several algorithms to filter and rank the information on Social Networking Sites (SNS). As a first step we identify the factors that impact user evaluations of information shared through these networks in a set of regression analyses. Second, we use a Neural Network algorithm to predict three dimensions of user evaluations: affective, cognitive and instrumental value of information shared. Moreover, we design algorithms that allow not only to filter out the irrelevant information, but also rank the information on SNS in order of its relevance. As a result, the filtering algorithm accurately predicts in 73% of the cases, whereas for more than 70% of the users the individual ranking accuracy lies over 70%. The designed algorithms can be implemented by SNS providers in order to present users with more relevant and better structured information

‘STOP SPAMMING ME!’ - Exploring Information Overload on Facebook

The problem of information overload on Facebook is exacerbating as users expand their networks. Growing quantity and increasingly poor quality of information on the Newsfeed may interfere with the hedonic experience of users resulting in frustration and dissatisfaction. In the long run, such developments threaten to undermine sustainability of the platform. To address these issues, our study adopts a grounded theory approach to explore the phenomenon of information overload on Facebook. We investigate main sources of information overload, identify strategies users adopt to deal with it as well as possible consequences. In-depth analysis of the phenomenon allows us to uncover individual peculiarities for identification of relevant information. Based on them we provide valuable recommendations for network providers

INVESTIGATION OF THE NETWORK CONSTRUCTION BEHAVIOR ON SOCIAL NETWORKING SITES

By enabling connections between individuals, Social Networking Sites, such as Facebook, promise to create significant individual as well as social value. Encouraging connections between users is also crucial for service providers who increasingly rely on social advertising and viral marketing campaigns as important sources of their revenue. Consequently, understanding user’s network construction behavior becomes critical. However, previous studies offer only few scattered insights into this research question. In order to fill this gap, we employ Grounded Theory methodology to derive a comprehensive model of network construction behavior on social networking sites. In the following step we assess two Structural Equation Models to gain refined insights into the motivation to send and accept friendship requests – two network expansion strategies. Based on our findings, we offer recommendations for social network providers

I LIKE IT BECAUSE I (‘M) LIKE YOU – MEASURING USER ATTITUDES TOWARDS INFORMATION ON FACEBOOK

Limited in motivation and cognitive ability to process the increasing amount of information on their Newsfeed, users apply heuristic processing to form their attitudes. Rather than extensively analysing the content, they increasingly rely on heuristic cues – such as the amount of comments and likes as well as the level of relationship with the “poster” – to process the incoming information. In the paper we explore what impact these heuristic cues have on the affective and cognitive attitude of users towards the posts on their Newsfeed. We conduct a survey on based on a Facebook application that allows users to evaluate Newsfeed posts in real time. Applying two distinct panel-regression methods we report robust results that indicate that there is a certain relationship primacy effect when users are processing information: only if the level of relationship with the “poster” is low, the impact of comments and likes on the attitude is considered, whereby likes trigger positive, whereas comments – negative evaluations

It’s All About Networking! Empirical Investigation of Social Capital Formation on Social Network Sites

As Social Network Sites (SNS) permeate our daily routines, the question whether participation results in value for SNS users becomes particularly acute. This study adopts a \u27participation-source-outcome\u27 perspective to explore how distinct uses of SNS generate various types of social capital benefits. Building on existing research, extensive qualitative findings and an empirical study with 253 Facebook users, we uncover the process of social capital formation on SNS. We find that even though active communication is an important prerequisite, it is the diversified network structure and the increased social connectedness that are responsible for the attainment of the four benefits of social capital on SNS: emotional support, networking value, horizon broadening and offline participation. Moreover, we propose and validate scales to measure social capital benefits in the novel context of SNS

‘Generation Facebook’ – A Cognitive Calculus Model of Teenage User Behavior on Social Network Sites

With the growing popularity of Facebook, the number of teenage users has significantly increased. Parents and teachersobserve this development critically as they fear that teenagers are prone to over-engage in pleasant activities and neglectthe risks connected with information revelation. This paper adopts an explorative approach in order to investigate whatmotivates and hinders teenagers to use SNS and how using this medium affects their identities. By applying GroundedTheory to analyze data obtained in interviews, we formulate a conceptual model of teenage behavior on Facebook. Wefind that teenagers behave rationally on SNS, consciously weighing the benefits against the costs and acting inaccordance with their preferences. Shared information and the diversified network structure allow teenagers to obtainsupport in school-related matters, broaden their horizon and intensify relationships with their peers. At the same time,peer and parental pressure play a significant role in this process

TamagoCar: Using a Simulation App to explore Price Elasticity of Demand for Electricity of Electric Vehicle Users

The integration of electric vehicles (EV) into the smart grid is bounded by high variability of demand for electricity, unwillingness of consumers to change behavior as well as low degree of product familiarity. Especially the absence of real-time energy tariffs constrains the widespread use of EVs as sustainable alternatives to a combustion engine. We propose to explore the behavior of EV users with a specifically designed application, TamagoCar, which combines the users’ real world driving behavior with a simulated EV environment. We hypothesize that the EV users will adjust their demand for electricity as a function of uncertainty about future price, range anxiety, uncertainty about future travel and social influence. With our application we enable the end users to gain experience with using an EV as well as adjust their electricity demand in response to real-time price changes with respect to their individual preferences, social influence and macroeconomic conditions

Modeling a Nociceptive Neuro-Immune Synapse Activated by ATP and 5-HT in Meninges : Novel Clues on Transduction of Chemical Signals Into Persistent or Rhythmic Neuronal Firing

Extracellular ATP and serotonin (5-HT) are powerful triggers of nociceptive firing in the meninges, a process supporting headache and whose cellular mechanisms are incompletely understood. The current study aimed to develop, with the neurosimulator NEURON, a novel approach to explore in silico the molecular determinants of the long-lasting, pulsatile nature of migraine attacks. The present model included ATP and 5-HT release, ATP diffusion and hydrolysis, 5-HT uptake, differential activation of ATP P2X or 5-HT3 receptors, and receptor subtype-specific desensitization. The model also tested the role of branched meningeal fibers with multiple release sites. Spike generation and propagation were simulated using variable contribution by potassium and sodium channels in a multi-compartment fiber environment. Multiple factors appeared important to ensure prolonged nociceptive firing potentially relevant to long-lasting pain. Crucial roles were observed in: (i) co-expression of ATP P2X2 and P2X3 receptor subunits; (ii) intrinsic activation/inactivation properties of sodium Nav1.8 channels; and (iii) temporal and spatial distribution of ATP/5-HT release sites along the branches of trigeminal nerve fibers. Based on these factors we could obtain either persistent activation of nociceptive firing or its periodic bursting mimicking the pulsating nature of pain. In summary, our model proposes a novel tool for the exploration of peripheral nociception to test the contribution of clinically relevant factors to headache including migraine pain.Peer reviewe