Gossip: Identifying Central Individuals in a Social Network

Banerjee, Abhijit; Chandrasekhar, Arun G.; Duflo, Esther; Jackson, Matthew O.

doi:10.2139/ssrn.2425379

Cited by 61 publications

(109 citation statements)

References 45 publications

(32 reference statements)

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“…An empirical illustration using microfinance-related data from Banerjee, Chandrasekhar, Duflo, and Jackson (2014) is also given. Both papers employ the assumption that a unique equilibrium is present in the data (even if the payoff structure is amenable to multiple solutions), which is not uncommon in the empirical games literature.…”

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confidence: 99%

Econometrics of network models

Paula¹

2016

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In this article I provide a (selective) review of the recent econometric literature on networks. I start with a discussion of developments in the econometrics of group interactions. I subsequently provide a description of statistical and econometric models for network formation and approaches for the joint determination of networks and interactions mediated through those networks. Finally, I give a very brief discussion of measurement issues in both outcomes and networks. My focus is on identification and computational issues, but estimation aspects are also discussed.

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confidence: 99%

Econometrics of network models

Paula¹

2016

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“…Studies have found that the proximity to the people in one's network is not as important as the stature of those people [59,76]. Therefore we assume that two-way interactions such as endorsements are preferred by farmers and provide a higher level of information acceptance compared with one-way interactions such as imitation.…”

Section: Network Approachmentioning

confidence: 97%

Simulation vs. Definition: Differing Approaches to Setting Probabilities for Agent Behaviour

Morgan

Brown

Daigneault

2015

Land

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While geographers and economists regularly work together on the development of land-use and land-cover change models, research on how differences in their modelling approaches affects the results is rare. Answering calls for more coordination between the two disciplines in order to build models that better represent the real world, we (two economists and a geographer) developed an economically grounded, spatially explicit, agent-based model to explore the effects of environmental policy on rural land use in New Zealand. This inter-disciplinary collaboration raised a number of differences in modelling approach. One key difference, and the focus of this paper, is the way in which processes that shape the behaviour of agents are integrated within the model. Using the model and a nationally representative survey, we compare the land-use effects of two disciplinary-aligned approaches to setting a farmer agent's likelihood of land-use conversion. While we anticipated that the approaches would significantly affect model outcomes, at a catchment scale they produced similar trends and results. However, further analysis at a sub-catchment scale suggests the approach to setting the likelihood of land-use conversion does matter. While the results outlined here will not fully resolve the disciplinary differences, they do outline the need to account for heterogeneity in the predicted agent behaviours for both disciplines. OPEN ACCESSLand 2015, 4 915

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“…Next, the difference between model values, obtained by model (1) and model (2), is defined, and the sum of the received quantities is calculated. The calculated indicator reflects the absolute value of the increase in the property being investigated.…”

Section: Advances In Economics Business and Management Research Volmentioning

confidence: 99%

“…• The study of propaganda methods, information wars, identification of the information distribution centers (for example, the source of gossip [2]). …”

Section: Introductionmentioning

confidence: 99%

Econometric models for evaluation of marketing activities` indicators of social network

Gribanova¹,

Shirenkov²,

Катасонова³

2017

Proceedings of the International Conference on Trends of Technologies and Innovations in Economic and Social Studies 2017

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Abstract-In recent years, the analysis of social networks has received considerable attention in the literature because they have a global reach and the large number of data available. For organizations, there are the social networks attractive from the perspective of the promotion of their products and services. And the successful implementation of these activities must take into account a number of factors, existing dependencies in the system and laws for its development. This article is dedicated to study of marketing activities in the social network. The main factors that can influence the result of economic activities are identified. For the study, the authors used data from the groups in the social network VKontakte in the city of Tomsk. For this purpose, the authors calculated network analysis metrics (a clustering factor, a degree, a number of second-level elements) and specific indicators of social groups (activity, popularity). A Java-based program was implemented to collect data and perform group metric calculations. Two regression models have been developed. Also different types of dependencies were studied: linear, hyperbolic, progressive. The first regression model describes the change dependency on the number of members of the group as a result of the competition, based on the number of subscribers and the popularity of the group. The second regression model describes how the value of the advertisement in the group is dependent on the number of subscribers and the indicator of whether the group is the "leader". Both regressions are significant at 99% confidence level. The models can be used in planning and evaluating the results of marketing activities.

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Gossip: Identifying Central Individuals in a Social Network

Cited by 61 publications

References 45 publications

Econometrics of network models

Econometrics of network models

Simulation vs. Definition: Differing Approaches to Setting Probabilities for Agent Behaviour

Econometric models for evaluation of marketing activities` indicators of social network

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