  Image of an entity can be defined as a structured and dynamic representation
which can be extracted from the opinions of a group of users or population.
Automatic extraction of such an image has certain importance in political
science and sociology related studies, e.g., when an extended inquiry from
large-scale data is required. We study the images of two politically
significant entities of France. These images are constructed by analyzing the
opinions collected from a well known social media called Twitter. Our goal is
to build a system which can be used to automatically extract the image of
entities over time.
  In this paper, we propose a novel evolutionary clustering method based on the
parametric link among Multinomial mixture models. First we propose the
formulation of a generalized model that establishes parametric links among the
Multinomial distributions. Afterward, we follow a model-based clustering
approach to explore different parametric sub-models and select the best model.
For the experiments, first we use synthetic temporal data. Next, we apply the
method to analyze the annotated social media data. Results show that the
proposed method is better than the state-of-the-art based on the common
evaluation metrics. Additionally, our method can provide interpretation about
the temporal evolution of the clusters.
