  This paper presents a new decision support system offered for an in-depth
analysis of semantic networks, which can provide insights for a better
exploration of a brand's image and the improvement of its connectivity. In
terms of network analysis, we show that this goal is achieved by solving an
extended version of the Maximum Betweenness Improvement problem, which includes
the possibility of considering adversarial nodes, constrained budgets, and
weighted networks - where connectivity improvement can be obtained by adding
links or increasing the weight of existing connections. Our contribution
includes a new algorithmic framework and the integration of this framework into
a software system called Brand Network Booster (BNB), which supports brand
connectivity evaluation and improvement. We present this new system together
with three case studies, and we also discuss its performance. Our tool and
approach are valuable to both network scholars and in facilitating strategic
decision-making processes for marketing and communication managers across
various sectors, be it public or private.
