We propose a methodology to construct a term dictionary for text analytics through an interactive process between a human and a machine. The interactive approach helps the creation of flexible dictionaries with precise granularity required in text analysis. This paper introduces the first formulation of interactive dictionary construction to address this issue. To optimize the interaction, we propose a new algorithm that effectively captures an analyst’s intention starting from only a small number of sample terms. Along with the algorithm, we also design an automatic evaluation framework that provides a systematic assessment of any interactive method for the dictionary creation task. Experiments using real scenario based corpora and dictionaries show that our algorithm outperforms baseline methods, and works even with a small number of interactions. Also, we provide our dataset for future studies.