2020 Kaleidoscope

SumUp Analytics
Oct 10 · 4 min read

Deciphering 2020 Election News Patterns [Week 1, 10/4/2019]

This newsletter is a weekly publication showcasing two simple applications of SumUp’s platform: an analysis of news pertaining to the 2020 elections and a technical review of research published on Computational linguistics.

393 days to the elections

What topics are most emphasized across the mainstream media’s coverage of the 2020 presidential election?

To find out, we ran 292 articles from 13 news feeds through the SumUp platform. SumUp analytics is initiating a weekly blog using text analytics technology developed over the last few years to extract key content from a representative sample of the 2020 elections news. All information used is freely and easily available on the web. We didn’t apply any filters. Keep in mind that these results are only representative of the 13 news sources listed at the bottom of this article.

This blog is not expressing an opinion but rather highlights the most relevant topics in the recent news coverage.

This initial analysis was executed using a representative sample of 13 news feeds (in annex), combining all articles available on the first page of these publications on 10/4/2019. Different information sources would yield a different output. We made an effort to be impartial when compiling the input sources but we encourage you to provide feedback. Additional analytics will be provided as this blog evolves.

SumUp 2020 key topics on 10/4/2019, by order of relevance

Topic 1: Joe Biden
Explanation: Joe Biden appears as the number 1 topic because his name is mentioned in a multitude of contexts, not because it appears in relation to one specific subject: it appears as part of the Trump/Biden discussion, as part of the fund raising discussion, or on its own in relation to his own campaigning effort.

Topic 2: Democratic and Republican primaries
Explanation: Primaries are mentioned often in politically neutral contexts, often in the context of state primaries.

Topic 3: Health care
Explanation: health care represents a significant part of the corpus analyzed, usually in the context of the democrats campaigning themes.

Topic 4: Impeachment
Explanation: impeachment does not appear in one single context. The 4th position seems to result from impeachment being mentioned around factual information: proceedings have started and many people related to the proceedings are mentioned (president Zelensky, president Trump, speaker Pelosi).

Topic 5: Pete Buttigieg
Explanation: Pete Buttigieg is mentioned in various contexts, the most frequent one being fundraising.

Topic 6: Climate change
Explanation: climate change is a theme often mentioned as part of democratic candidates agendas.

Topic 7: Black voters
Explanation: black voters are mentioned in the context of their support for the established wing of the democratic party, Biden today, Clinton in the past and their hesitation to support the liberal wing, Sanders and Warren today.

Topic 8: Polk County
Explanation: Polk County appears in the context of numerous candidate visits.

These topics are only representative of the key subjects appearing in the sources of information reviewed by Nucleus. A more refined interpretation, in terms of content or order of importance is left to the reader and could easily be pursued with the Nucleus platform. In order to facilitate that analysis, we added the actual Nucleus analysis to the annex, providing further measure of sentiment attached to each of these topics, or summary explanation of each topic.

Annex 1 Election 2020 news sources:
https://www.theguardian.com/us-news/us-elections-2020 https://fivethirtyeight.com/politics/elections/ https://www.chicagotribune.com/politics/elections/ https://www.politico.com/news/2020-elections https://www.cnn.com/specials/politics/2020-election-coverage https://time.com/5675691/2020-election-candidates-website-disability-accessibility/ https://www.newyorker.com/tag/2020-election https://www.foxnews.com/category/politics/2020-presidential-election https://www.usatoday.com/search/?q=2020%20democratic%20elections https://www.washingtonexaminer.com/tag/2020-elections https://www.washingtontimes.com/elections/ https://www.vox.com/2020-presidential-election https://www.breitbart.com/tag/2020-election/

Computational Linguistic Research Week of 9/30/2019

Leveraging its text analytics platform, SumUp has designed a simple method to rank recent research publications, purely based on their relation to the top topics extracted from these publications. Creating a corpus composed of all recent publications (all publications published on arxiv.org over the last week), nucleus extracts 8 key topics representative of that research corpus. Nucleus then identifies the top documents related to these topics. SumUp ranks articles, according to the number of times each article is mentioned in the 8 extracted topics.

Using the corpus composed of articles published during the week of the 30th September 2019, the following 8 key topics are extracted:

[Machine translation] [RNN/CNN] [word embeddings] [speech signals] [sentiment] [social media] [leaning][parallel computations]

Using SumUp ranking methodology, the following articles are most representative of the top 8 topics of the week of 9/30/2019:

Self-Attention Transducers for End-to-End Speech Recognition Zhengkun Tian , Jiangyan Yi , Jianhua Tao , Ye Bai , Zhengqi Wen

This article is mentioned in relation to machine translation, word embeddings and parallel computation.

The Source-Target Domain Mismatch Problem in Machine Translation Jiajun Shen, Peng-Jen, Chen Matt, Le Junxian, He Jiatao, Gu Myle, Ott Michael Auli, Marc’Aurelio Ranzato
This article is mentioned in relation to CNN/RNN, speech signal, social media.

All other articles published during the period under review are related to at most 2 topics and in most cases to less.

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