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paper/paper.md

@@ -36,9 +36,9 @@ For many users, these tools offer the necessary functionality to visualize netwo
 *Netwulf* is a light-weight Python library that provides a simple API for interactively visualizing a network and returning the computed layout and style. It is build around the philosophy that network manipulation and preprocessing should be done programmatically, but that the efficient generation of a visually appealing network is best done interactively, without code. Therefore, it offers no analysis functionality and only few exploration features, but instead focuses almost entirely on fast and intuitive layout manipulation and node/link styling. Interaction with Netwulf typically works as follows:
 
 1. Users have a network object, `G`, in either dictionary or *networkx.Graph* format. They then launch a Netwulf visualization by calling `netwulf.visualize(G)`.
-2. The command opens a new browser window containing `G` as an interactive, manipulable, stylable network. Here, the user can for instance explore how different configurations of physics parameters like *node charge* and *gravity* influence the layout, they can change properties like node color and link opacity, and even threshold the network data for weak or strong links. When the user has finalized the layouting process, they may either:
+2. The command opens a new browser window containing `G` as an interactive, manipulable, stylable network. Here, the user can, for instance, explore how different configurations of physics parameters like *node charge* and *gravity* influence the layout, they can change properties like node color and link opacity, and even threshold the network data for weak or strong links. When the user has finalized the layouting process, they may either:
    1. Save the image directly from the interactive visualization as a PNG file.
-   2. Post the style and computed node positions back to Python in a dictionary format, which allows for further manipulation in the Python backend. Moreover, using the function `netwulf.draw_netwulf`, the network can be redrawn using the common Python drawing library matplotlib [@matplotlib], which further enables saving the visualization in any format.
+   2. Post the style and computed node positions back to Python in a dictionary format, which allows for further manipulation in the Python backend. Moreover, using the function `netwulf.draw_netwulf`, the network can be redrawn using the common Python drawing library *matplotlib* [@matplotlib], which further enables saving the visualization in any format.
 
 The interactive visualization is implemented in JavaScript, relies on d3.js [@d3] for computing layouts, and uses the HTML5-object `canvas` for rendering. This makes it, to our knowledge, the most performant tool for interactive network visualization in Python to date.