Hi Samiya,

We have to be careful. This uses a technique usually referred to as
"sentiment analysis" and sometimes as "opinion mining". There is extensive
research on using it for things like election forecasting, and the results
are not exactly encouraging...

The idea is very interesting in itself, but the current methods are quite
limited. The common approaches are:

1) Using a dictionary where every word is annotated by humans in terms of a
score for each base emotion, do a lookup for the entire text and present
the final summation;

2) Using machine learning to train a model to recognize emotions taking
into account n-grams, instead of a single word.

The first method is very naif, many words have quite different emotional
valencies depending on context. It also fails to detect sarcasm and other
complexities of human language.

The second method could in principle work much better, but it requires a
large corpus of text annotated by emotional valencies. Such corpora exist
for specific applications, but models trained that way tend to not work
when you deviate too much from the context of the training data. Religious
texts are most likely too far away from any useful training corpora.

Worse still, we are comparing translations from vastly different cultures
and linguistic backgrounds.

Some people suspect (me included) that producing a reliable sentiment
analysis algorithm requires solving the general problem of AI.

Best,
Telmo.

On Tue, Feb 9, 2016 at 6:01 PM, Samiya Illias <[email protected]>
wrote:

> Bible, Quran and Violence
> Software uses scripture to show what text analysis can do:
> http://m.toledoblade.com/Religion/2016/02/06/The-Bible-the-Qur-an-and-violence-computerized.html
>
>
> Samiya
>
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