From the Hands of an Early Adopter's Avatar to Virtual Junkyards: Analysis of Virtual Goods' Lifetime Survival

One of the major questions in the study of economics, logistics, and business forecasting is the measurement and prediction of value creation, distribution, and lifetime in the form of goods. In "real" economies, a perfect model for the circulation of goods is impossible. However, virtual realities and economies pose a new frontier for the broad study of economics, since every good and transaction can be accurately tracked. Therefore, models that predict goods' circulation can be tested and confirmed before their introduction to "real life" and other scenarios. The present study is focused on the characteristics of early-stage adopters for virtual goods, and how they predict the lifespan of the goods. We employ machine learning and decision trees as the basis of our prediction models. Results provide evidence that the prediction of the lifespan of virtual objects is possible based just on data from early holders of those objects. Overall, communication and social activity are the main drivers for the effective propagation of virtual goods, and they are the most expected characteristics of early adopters.Comment: 28 page

Modeling the impact of the habituation effect on information spreading processes with repeated contacts under an SI model.

People are exposed to information from different sources whether or not such exposure is desired. Due to a limited ability to process information, only parts of the messages may be absorbed, and other parts may be ignored. Repeated stimuli lead to lower responses due to the learning process and the habituation effect. While this effect has been intensively studied, mainly in relation to visual stimulus, it is also incorporated in information spreading processes. Information spreading models often assume the possibility of repeated contact, but no habituation effect, which lowers the level of responsiveness of nodes in the network, has been implemented. Here, we study the impact of the habituation effect on information spreading with a susceptible-infected (SI) model, which is often the basis for other models. We assume that a decrease in habituation has an impact on propagation processes. Analysis of the results shows that the course of these propagation processes behave differently, significantly worsening their results. These processes are very sensitive, even to small changes in the level of habituation

Fig 4 -

(A1) Coverage for spreading processes with and without habituation. (A2) Coverage decrease in processes with the habituation effect, compared to processes without habituation, sorted by the decrease in coverage. (A3--A5) Distances between coverage in simulations with and without the habituation effect, with results sorted by coverage without habituation and assigned corresponding results from processes with the habituation effect. (B1) Coverage for each network for spreading processes with and without habituation. (B2) Decrease in coverage for each network in relation to a process without habituation. (C1) Coverage for each alpha value for spreading processes with habituation compared to a process without habituation. (C2) Decrease in coverage for each alpha in relation to a process without habituation. (D1) Coverage for propagation probabilities for spreading processes with and without habituation. (D2) Decrease in coverage for each PP value in relation to a process without habituation. (E1) Coverage for each seeding percentage for spreading processes with and without habituation. (E2) Decrease in coverage for each SP in relation to a process without habituation. (F1) Coverage for each tau value for spreading processes with habituation in comparison with processes without habituation. (F2) Decrease in coverage for each tau in relation to a process without habituation.</p

Example illustrating the impact of repeated ineffective/unwanted contacts on node responsiveness.

Example illustrating the impact of repeated ineffective/unwanted contacts on node responsiveness.</p

Coverage for spreading processes with and without habituation.

Coverage for spreading processes with and without habituation.</p

Coverage decrease for spreading processes with the habituation effect.

Coverage decrease for spreading processes with the habituation effect.</p

Fig 5 -

(A) Coverage for each network for all spreading processes without habituation. (B) Coverage for each network for all spreading processes with habituation. (C1) Coverage for each network for spreading processes with the “worst” set of habituation parameters. (C2) Decrease in coverage for each network in relation to a process without habituation with the “worst” habituation parameters. (D1) Coverage for each network for spreading processes with the “best” set of habituation parameters.(D2) Decrease in coverage for each network in relation to a process without habituation with the “best” habituation parameters.</p

Duration for spreading processes with and without habituation.

Duration for spreading processes with and without habituation.</p

Duration increase for spreading processes with the habituation effect.

Duration increase for spreading processes with the habituation effect.</p

Parameters used for diffusion in the simulations.

People are exposed to information from different sources whether or not such exposure is desired. Due to a limited ability to process information, only parts of the messages may be absorbed, and other parts may be ignored. Repeated stimuli lead to lower responses due to the learning process and the habituation effect. While this effect has been intensively studied, mainly in relation to visual stimulus, it is also incorporated in information spreading processes. Information spreading models often assume the possibility of repeated contact, but no habituation effect, which lowers the level of responsiveness of nodes in the network, has been implemented. Here, we study the impact of the habituation effect on information spreading with a susceptible–infected (SI) model, which is often the basis for other models. We assume that a decrease in habituation has an impact on propagation processes. Analysis of the results shows that the course of these propagation processes behave differently, significantly worsening their results. These processes are very sensitive, even to small changes in the level of habituation.</div