[Corpora-List] EmoText - Software for opinion mining and lexical affect sensing

[Alexander Osherenko]

The initial question was: is it necessary to compose separate datasets for
opinion mining in English British, in American English, in Australian
English etc or there is some sort of universal dataset that can be used for
opinion mining in every English. As far as I understood, Justin thinks
there is the universal dataset. I am convinced that only language
consideration is not enough and there must be other factors that influence
feature extraction. I assumed this influence can be represented by
geographical reasons. Moreover, I supposed that weights of features in
classifiers are more appropriate to explain pragmatic content of a text and
not semantic.

2011/12/22 Yorick Wilks <Y.Wilks at dcs.shef.ac.uk>

> Surely, the point this interchange has reached has nothing to do with
> country or variants of a language of the kind a linguist is interested in;
> for "American truck driver" substitute "local physicist". This has gone
> into areas where linguistics and NLP have nothing to say if "comprehension"
> is extended to mean "understands mathematics".
> Yorick Wilks
>
>
> On 22 Dec 2011, at 16:26, Alexander Osherenko wrote:
>
> Justin,
>
> I mean more the distinction between pragmatics and semantics (
> http://oxfordbibliographiesonline.com/view/document/obo-9780195396577/obo-9780195396577-0146.xml#obo-9780195396577-0146-div1-0010
> )
>
> AO
>
> 2011/12/21 Justin Washtell <lec3jrw at leeds.ac.uk>
>
>> Hello Alexander,
>>
>> >> As a human, and an Englishman, I expect I can understand and fairly
>> judge the sentiment of most reviews written by, say, an American truck
>> driver, without undue reprogramming. Is this really an unrealistic goal for
>> our algorithms? And I wonder, is mastering a highly restricted style or
>> register a necessary step in that direction... or is it in fact a detour.
>> > As a human and as an Englishman, you learned to recognize particular
>> words of English language. Now you understand English in every country but
>> you can't comprehend it. Understanding is only the first step of cognition,
>> comprehension takes much more time and energy. Or can you explain the most
>> severe problems of American truck drivers nowadays? Or tell me what
>> problems you would discuss with an American truck driver? In terms of data
>> mining, it means: you know what features you have in a dataset but you
>> don't know their weights. In my opinion, if you want to learn "weights" you
>> have to live in the country and tune the weights.
>>
>> I was referring only to detecting coarse-grained sentiment, not to
>> appreciating the detailed tribulations of the author's lifestyle, but you
>> make a point :-) The distinction you draw between understanding and
>> comprehension is an unfamiliar one to me. I'm not sure whether it is more
>> akin to the distinction I would make between "recognition" and
>> "understanding", or between "undestanding" and "experiencing" (though both
>> of which I concede are fuzzy at best and lure us beyond the pretentiously
>> tidy realms of NLP and into the free-for-all that is philosophy). In any
>> case, please re-interpret my use of the word to mean something closer to
>> what you would call "comprehension".
>>
>> Justin
>>
>
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