We present NodeXL, an extendible toolkit for network overview, discovery and exploration implemented as an add-in to the Microsoft Excel 2007 spreadsheet software. We demonstrate NodeXL data analysis and visualization features with a social media data sample drawn from an enterprise intranet social network. A sequence of NodeXL operations from data import to computation of network statistics and refinement of network visualization through sorting, filtering, and clustering functions is described. These operations reveal sociologically relevant differences in the patterns of interconnection among employee participants in the social media space. The tool and method can be broadly applied.

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Social media platforms provide people all over the world with an unprecedented ability to organize around social and political causes. However, these same platforms enable institutional and organized actors to engineer fabricated social movements to advance their agenda. These “astroturfing” or “false amplification” phenomenons leverage a variety of of tools and techniques, ranging from fully automated bot activity to accounts manned by extrinsically motivated (e.g. compensated) human operators. These campaigns also range from simple spam operations to sophisticated efforts involving numerous orchestrated accounts, sometimes coordinated across linguistic and cultural clusters. While the former category is straightforward to analyze via data mining methods, sophisticated fabricated campaigns in the latter category are engineered to mask their true nature from the public.Working from the proposition that a large number of accounts controlled by a small number of coordinated entities will lack the behavioral diversity of a similar number of accounts controlled by uncoordinated individual actors, we propose a framework of signals (metrics) along three dimensions: Network: how accounts are connected to one another, and the clusters they form within the online conversation, Temporal: patterns of messaging across time in the online conversation, Semantic: an observation of the diversity of topics and meaning throughout the online conversation.We test this framework on three case studies: the online conversation on #ColumbianChemicals in the U.S., the international discussion of the #DopingLeaks event, and an analysis of political discussions in Venezuela. In all three cases, we find what we assess to be anomalous, fabricated behavior on at least one dimension.

The ability to utilize and benefit from today's explosion of social media sites depends on providing tools that allow users to productively participate. In order to participate, users must be able to find resources (both people and information) that they find valuable. Here, we argue that in order to do this effectively, we should make use of a user's "social context". A user's social context includes both their personal social context (their friends and the communities to which they belong) and their community social context (their role and identity in different communities).

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