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Topogram: a Web Toolkit
for Spatio-Temporal Network Mapping
Clément Renaud
I3 - Telecom ParisTech
[email protected]
Grégory Bahde
Université Jean Monnet St Etienne
[email protected]
Topogram is a web-based and open-source toolkit to extract and visualize social, semantic and
spatio-temporal dynamics within large sets of data. The methodological concept of "topogram"
offers to describe activities in data by different dimensions: words (lexical analysis), relationships
(networks), time (changes and evolution) and space (geographic mapping). By providing a
framework to extract and visualize socio-semantic and spatio-temporal information, Topogram
wants to create a broader space for representation of complex phenomena.
Created for the study of Internet memes spread in the context of a Chinese social network (Renaud,
2014; Renaud & al., 2016), Topogram originates in an effort to provide a data mining and
visualization framework that allows researchers to minimize routine tasks and focus on the
exploration of relationships between dimensions in data. Topogram interface is designed
hierarchically to minimize user information overload with the specific purpose of helping users with
no technical background to apprehend network and semantic analysis. The web interface also allows
for real-time edition and annotation of a single document by multiple users, making easy for teams
to work together on the analysis of large documents.
Users can import data containing text, dates and locations by using Topogram’s generic importer
(CSV files) or custom API scripts. Topogram server will process the data to extract a network of
words (text analysis) and citations (defined by regular expressions). Results will be indexed to allow
full-text search by terms, time and places. In Topogram, the text analysis is based on a plugin system
to easily allow multiples languages to be used. Currently English, French and Chinese language are
Figure 1: This interface allows a user to describe a dataset he has uploaded
Once information have been extracted from the data, the visualization interface allow a browsing
with different views: a network of words based on lexical analysis (word cooccurrences), a
representation of time distribution in the data (interactive bar graph), a geographical map of the
provided locations and potentially a network graph of other entities extracted from the data (ex.
citations graph in social networks). Data can be browsed through any of those different dimensions:
selection of a specific timeframe or geographic zone, lookup of specific words and terms, selection
of parts of the graph, etc. Each selection criteria will update other views of the data accordingly,
allowing an easy exploration of the data. Figures and results can be exported easily as images (png or
svg), subsets of data (csv) or web-view by sharing directly a URL to the visualisation.
Figure 2: This figure is a screenshot of Topogram visualization view for data exploration,
Renaud, C. (2014). Conception d’un outil d’analyse et de visualisation des mèmes Internet. Telecom ParisTech.
Renaud, C., Puel, G., & Fernandez, V. (2016) Topogrammes: les mèmes Internet ont-ils un mode de
propagation spécifique ? Réseaux (195)