Comments on: Sentiment Analysis best done by humans

By: El Mito de los Software de Inteligencia Competitiva: Automatización vs Inteligencia « Fin del Marketing.com

Fri, 17 Sep 2010 20:14:51 +0000

[...] Hace unas semanas, Hugo Zunzarren (colega y experto en Inteligencia Competitiva) nos presentaba un post en el cual hacía mención a las falsas expectativas que generan en el mercado quienes comercializan este tipo de software, fundamentalmente cuando nos enfrentamos con información cualitativa, hoy en auge para el análisis de las Redes Sociales. A menos que exista evidencia explicita, un robot no es capaz de discernir si un comentario tiene connotación positiva, neutra o negativa (a pesar de que se está insistiendo con cierto éxito en algoritmos que se aproximen a los resultados ciertos), ya que este no solo depende de las palabras en sí mismas, sino del contexto y del tono del comentario. Hugo concluía en la escasa fiabilidad de los análisis automáticos, citando la afirmación categórica de Jason Falls y Marshall Sponders, expertos en la medición cualitativa de los mensajes: el análisis lo hace mejor un humano. [...]

By: business grant

business grant — Wed, 08 Sep 2010 13:54:27 +0000

This is interesting because a tool is available to measure sentiments of people. It will help predict behavior or specific persons given a certain stimuli.

By: Why analytics companies should stop focusing on “accuracy” in automated sentiment analysis | Beyond

Fri, 27 Aug 2010 17:56:01 +0000

[...] new tool can identify sentiment “better than most humans”. Just a few days later, I read a post this week claiming that ”sentiment analysis [is] best done by [...]

By: Babar Bhatti

Babar Bhatti — Sun, 25 Jul 2010 03:11:24 +0000

Having human oversight is vital for sentiment analysis. But automated sentiment analysis can work much better if you understand how to use it correctly. Here’s my blog post on how to effectively use today’s technology to make the best of sentiment analysis:
http://www.mutualmind.com/blog/2010/07/10-ways-effectively-use-sentiment-analysis-social-media/

Babar
Founder, MutualMind.

By: Iason Demiros

Iason Demiros — Tue, 18 May 2010 07:14:06 +0000

This is a nice post and the presentation as well. Far from solved, this is a very difficult problem that requires pragmatics and world knowledge, humour analysis and treatment of advanced phenomena such as ellipsis, among other natural language understanding tasks. It is – at least until now – a machine assisted task rather than a fully automated one. However progress so far leaves room for improvement and for optimism, especially at a macroscopic (aka document or multi-document) level.

Iason Demiros
QUALIA

By: WebMetricsGuru » Is there any point to doing Sentiment Analysis?

WebMetricsGuru » Is there any point to doing Sentiment Analysis? — Sat, 15 May 2010 15:10:48 +0000

[...] new tool can identify sentiment “better than most humans”. Just a few days later, I read a post this week claiming that ”sentiment analysis [is] best done by [...]

By: Why analytics companies should stop focusing on “accuracy” in automated sentiment analysis | context analytics

Fri, 14 May 2010 16:35:27 +0000

[...] new tool can identify sentiment “better than most humans”. Just a few days later, I read a post this week claiming that ”sentiment analysis [is] best done by [...]

By: Text Classification for Sentiment Analysis – Naive Bayes Classifier «streamhacker.com

Mon, 10 May 2010 14:32:46 +0000

[...] assumptions and very little code we're able to get almost 73% accuracy. This is somewhat near human accuracy, as apparently people agree on sentiment only around 80% of the time. Future articles in this [...]

By: Text Classification for Sentiment Analysis – Naive Bayes Classifier «streamhacker.com

Mon, 10 May 2010 14:32:46 +0000

By: Glueberry Pie

Glueberry Pie — Mon, 10 May 2010 10:46:04 +0000

I’m doing quite a lot of buzzmonitoring for brands and of course use automated tool. It only helps to measure the amount of mentions. To be honest the sentiment is not often accurate. Because when people use irony or humor, the data is the opposite sentiment. The human checking is an absolute necessity.