Re: The DATA Act, Department of the Treasury, and Machine Learning Technologies

Gannon,

 

I wanted to clarify, on the metadiscursive thread, that my expression about linguistics observations, topics, was pertinent to my own participation, that is, I would tend not to want to participate in dialogues which differ from, language ideologically, the preferences which I am indicating, which include rhetorical structure towards scientific discourse and argumentation, and, that said, others may, of course, use language as per their druthers and those of others in group dialogues.

 



Reiterating, hypotheses with regard to some linguistics observations, at the W3C and elsewhere, include: (1) scientists are concerned about surveillence, (2) computer scientists type, occupationally, in addition to uses of written language in communication.

  

Beyond this conversation, “tweets” are irritating to me, in particular when combined with figurative uses of language, high-context tweets, as are puns on technical nouns and technical verbifications.  Beyond language ideology and preferences, however, topics include productive users of language in scientific groups as well as language education.  Critics of Twitter, including some proponents of argumentation technology, might argue that Twitter encourages discussion of opinion without facilitating explanation or argumentation.

 


Furthermore, should we worry that education system administrators are receiving one-sided information from the marketing teams of technology products?  Are education administrators strolling amidst the shelves of scientific libraries or the booths at a trade expo?  When those attempting to present other points of view risk becoming unpopular, how are the education administrators well-informed?

 

 

 

Kind regards,

 

Adam

 

 

 




Fischer, Eileen, and A. Rebecca Reuber. "Social interaction via new social media: (How) can interactions on Twitter affect effectual thinking and behavior?." Journal of business venturing 26.1 (2011): 1-18.

 

Naone, Erica. "Twitter Reveals Business Model." MIT Technology Review (2010). Web.

 

Pak, Alexander, and Patrick Paroubek. "Twitter as a Corpus for Sentiment Analysis and Opinion Mining." LREC. 2010.

 


Park, Chang Sup. "Does Twitter motivate involvement in politics? Tweeting, opinion leadership, and political engagement." Computers in Human Behavior 29.4 (2013): 1641-1648.

 



Tumasjan, Andranik, et al. "Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment." ICWSM 10 (2010): 178-185.

Received on Monday, 16 September 2013 20:16:46 UTC