## 4 Sample Corpus Analysis
### U.S. Senate Hearings  
Figure 3 shows the analysis of the US Senate Hearings Committee on Environment and Public Works [53]. The corpus has 73 documents with an average of 15,605 tokens each. Each document is a verbatim transcript of a senate hearing session and the time stamp corresponds to the day the hearing. The corpus analysis of traditional term-frequency-based tools would be difficult because the corpus includes a variety of presentation styles, the documents use inconsistent lexical sets, and the legislative session covered a variety of topics of discussion. The transcript documents contain a variety of presentation formats from a dialogue between two or more U.S. Senate representatives, a testimonial from a single speaker, a piece of evidence submitted to the committee, and errata documents, to name a few. Unlike a single piece of writing that assumes a consistent lexical set used throughout the document, the hearing transcripts consist of sources from various individuals, and the consistency of lexical set used throughout the document cannot be assumed with the exception of the key topic tokens. For example one of the topics of discussion was the economic and ecological impact on Alaska's salmon fisheries in the context of oil production. The dialogue interchangeably used _fish_, _salmon_, and _sockey_ words to reference the same noun for the fish species of concern that should be represented by a single token. As a result, the analysis of the 2015-2016 U.S. Senate Hearings on Environment and Public Works meeting transcripts shows a much larger range of semantic concepts than the analysis of the [PERSON] novel. The connectivity and temporal dynamics of the semantic flows is much richer with inter- and intra-edges and numerous local semantic flows that propagate concepts across a small number of adjacent documents. Unlike the [PERSON] novel, the US Senate Hearings do not have just one common topic or a plot, instead the hearings discuss a large number of semantic concepts that fall into the _environment_ and _public works_ topics, how they relate to each other, and which topics are carried over the legislative holidays. The topic catalysts, where multiple topics merge only to break apart in the subsequent document include _financial_, _environment_, _congress_, _ResourcesDistricts_, _pollutant_ semantic concepts. The semantic concepts surrounding the catalysts are contents and issue-based with associate flows such as _oil_, _resources_, _dangerous_, _mineral_. The semantic flows also include semantic concepts expressing sentiment and connotation which include _doubtful_, _opportunity_ and _easier_. In a true exploratory fashion, we were interested in the areas of concerns and topics associated with fisheries. The two main semantic concepts that merged into the _fish_ semantic concept were _exempt_ with associated tokens _senatorbooker_, _private_, _build_, _continue_ and _senatormerkely_ with associated tokens _time_, _use_, _public_, _water_. Although the preceding semantic concept merged into the semantic concept _fish_ with supporting tokens _streamprotectionrule_, _health_, _require_, they also split, and were related, to other semantic concepts that appeared and were inter-connected to the _fish_ semantic concept, namely _protect_ with associated tokens _stream_, _mine_, _water_, _coal_, _mountaintop_ with associated tokens _senatorcapito_, _environ_, _response_, _surfac_, _pollut_, _meeet_, _develop_, _industrialstrand_ and _last_ with associated tokens _senatormarkedy_, _rulemake_, _last_, _alaska_, _study_, _compani_, _conit_, _establish_. The semantic concepts _fish_, _protect_, _mountaintop_ and _last_ fell into the following semantic concepts in the subsequent document: _propos_, _public_, _wildlife_, _right_, _conserv_, and _import_. The observations above confirm SNAP's ability to \"sieve\" the documents in the corpus of interest and distill the main concepts and their relations to the preceding and subsequent documents.