Mitigating Overexposure in Viral Marketing

In traditional models for word-of-mouth recommendations and viral marketing, the objective function has generally been based on reaching as many people as possible. However, a number of studies have shown that the indiscriminate spread of a product by word-of-mouth can result in overexposure, reaching people who evaluate it negatively. This can lead to an effect in which the over-promotion of a product can produce negative reputational effects, by reaching a part of the audience that is not receptive to it. How should one make use of social influence when there is a risk of overexposure? In this paper, we develop and analyze a theoretical model for this process; we show how it captures a number of the qualitative phenomena associated with overexposure, and for the main formulation of our model, we provide a polynomial-time algorithm to find the optimal marketing strategy. We also present simulations of the model on real network topologies, quantifying the extent to which our optimal strategies outperform natural baselinesComment: In AAAI-1

Sticky Seeding in Discrete-Time Reversible-Threshold Networks

When nodes can repeatedly update their behavior (as in agent-based models from computational social science or repeated-game play settings) the problem of optimal network seeding becomes very complex. For a popular spreading-phenomena model of binary-behavior updating based on thresholds of adoption among neighbors, we consider several planning problems in the design of \textit{Sticky Interventions}: when adoption decisions are reversible, the planner aims to find a Seed Set where temporary intervention leads to long-term behavior change. We prove that completely converting a network at minimum cost is $\Omega(\ln (OPT) )$-hard to approximate and that maximizing conversion subject to a budget is $(1-\frac{1}{e})$-hard to approximate. Optimization heuristics which rely on many objective function evaluations may still be practical, particularly in relatively-sparse networks: we prove that the long-term impact of a Seed Set can be evaluated in $O(|E|^2)$ operations. For a more descriptive model variant in which some neighbors may be more influential than others, we show that under integer edge weights from $\{0,1,2,...,k\}$ objective function evaluation requires only $O(k|E|^2)$ operations. These operation bounds are based on improvements we give for bounds on time-steps-to-convergence under discrete-time reversible-threshold updates in networks.Comment: 19 pages, 2 figure

Opinion dynamics with varying susceptibility to persuasion

A long line of work in social psychology has studied variations in people's susceptibility to persuasion -- the extent to which they are willing to modify their opinions on a topic. This body of literature suggests an interesting perspective on theoretical models of opinion formation by interacting parties in a network: in addition to considering interventions that directly modify people's intrinsic opinions, it is also natural to consider interventions that modify people's susceptibility to persuasion. In this work, we adopt a popular model for social opinion dynamics, and we formalize the opinion maximization and minimization problems where interventions happen at the level of susceptibility. We show that modeling interventions at the level of susceptibility lead to an interesting family of new questions in network opinion dynamics. We find that the questions are quite different depending on whether there is an overall budget constraining the number of agents we can target or not. We give a polynomial-time algorithm for finding the optimal target-set to optimize the sum of opinions when there are no budget constraints on the size of the target-set. We show that this problem is NP-hard when there is a budget, and that the objective function is neither submodular nor supermodular. Finally, we propose a heuristic for the budgeted opinion optimization and show its efficacy at finding target-sets that optimize the sum of opinions compared on real world networks, including a Twitter network with real opinion estimates

Incentivizing Exploration with Heterogeneous Value of Money

Recently, Frazier et al. proposed a natural model for crowdsourced exploration of different a priori unknown options: a principal is interested in the long-term welfare of a population of agents who arrive one by one in a multi-armed bandit setting. However, each agent is myopic, so in order to incentivize him to explore options with better long-term prospects, the principal must offer the agent money. Frazier et al. showed that a simple class of policies called time-expanded are optimal in the worst case, and characterized their budget-reward tradeoff. The previous work assumed that all agents are equally and uniformly susceptible to financial incentives. In reality, agents may have different utility for money. We therefore extend the model of Frazier et al. to allow agents that have heterogeneous and non-linear utilities for money. The principal is informed of the agent's tradeoff via a signal that could be more or less informative. Our main result is to show that a convex program can be used to derive a signal-dependent time-expanded policy which achieves the best possible Lagrangian reward in the worst case. The worst-case guarantee is matched by so-called "Diamonds in the Rough" instances; the proof that the guarantees match is based on showing that two different convex programs have the same optimal solution for these specific instances. These results also extend to the budgeted case as in Frazier et al. We also show that the optimal policy is monotone with respect to information, i.e., the approximation ratio of the optimal policy improves as the signals become more informative.Comment: WINE 201

Determinants and consequences of budget reallocations

We investigate the determinants and consequences of budget reallocations, i.e., corrective actions to the budget made during the year. Using proprietary data of a large consumer goods manufacturer, we analyze the extent to which allocation decisions regarding the initial budget drive subsequent reallocations. Whenever scarce resources need to be allocated among a number of individuals, power struggles and politicking behavior are likely to arise, which potentially affects the outcome of the allocation process. We hypothesize and find that one important driver of reallocation decisions is the firm's aim to correct for systematic deviations from the optimal initial budget allocation that are driven by successful lobbying activities during the initial budgeting process. In a more exploratory analysis, we show that such reallocations do not have the desired effects on market-place performance. In particular, budget cuts are negatively associated with a product's change in market share. More surprisingly, while budget boosts do help product lines internally to achieve their sales targets in the last quarter, they do not have a (positive) effect on the change in market share. Most importantly, our results demonstrate that efficient investment planning ex ante is essential to achieve an improvement in market-place performance, highlighting the value of budgeting.Series: Department of Strategy and Innovation Working Paper Serie

Devolved school-based financial management in New Zealand : observations on the conformity patterns of school organisations to change

This paper examines the intent and consequences of ‘new’ financial management (the ‘New Public Financial Management’) (NPFM) procedures invoked to facilitate a macro-micro interface within the context of the significant administrative reform of the New Zealand (NZ) state education system. The 1989 administrative reform of the NZ education system was predicated on a particular view of public sector management, which was characterised by the umbrella heading of ‘New Public Management’ (NPM). It was claimed that NPFM provided a link between the sets of values highlighted through the NPM reform process and the internal workings of various public sector organisations. The study provides case studies of the organisational financial management practices of four schools, some ten years after the reform. The observed practices are analysed and interpreted within a theoretical framework comprising two competing theories of change – NPM which provides the ‘normative’ intent for public sector organisational change, and institutional theory that offers an explanation of the ‘operational’ consequences of public sector organisational (i.e. schools) response to change. The findings suggest that accounting and management technologies have served a useful, political purpose, although not in the way espoused by NPM proponents

Arts for All: 5th Year Review

In September 2002, the Los Angeles County Board of Supervisors adopted Arts for All: Los Angeles County Regional Blueprint for Arts Education, a ten-year strategic plan to restore arts education -- in dance, music, theatre, and the visual arts -- to the 1.7 million students in Los Angeles County's 80 school districts and Los Angeles County Office of Education (LACOE) classrooms. The Arts for All Executive Committee, with more than 100 partners and supported by the Los Angeles County Arts Commission, leads this effort. The initiative, now in its fifth year, has made great strides