In an era where we are creating brain controlled airplanes, neurogaming, and robots that learn behavior by reading human emotions, there appear to be no limits in having search engines read human emotions in order to improve search results based on the neurological feedback they receive from user’s brain waves. Thanks to companies such as Interaxon and Emotiv, EEG devices have readily been made available to researchers interested in neuro-related studies, who otherwise would have not had access to expensive fMRI machines. Although the two devices measure different entities of the brain, nonetheless, EEG devices help enthusiastic, but low budget, researchers (such as me!) conduct neuro-related studies.
My doctoral research topic aims to examine cognitive relationships between dimensions of human emotions and information retrieval, as in search performance, in the field of neuro information science (Gwizdka, 2012). This study aims to increase our understanding in regards to affective search, improving information systems design practices, and investigating ways to design ‘smart’ information systems that learn and improve search results based on neuro feedback.
To illustrate, emerging expressions, such as “pleasurable engineering” or “emotional design”, have not only become the driving factors in information retrieval system design (Nahl & Bilal, 2007) but also illustrate the important role of emotions in human-computer-interaction. Information retrieval entails complicated cognitive processes, composed of human cognitive processes as well as human physiological and neurological reactions (Picard, 2001). However, our understanding of how emotions affect information retrieval is limited (Nahl & Bilal, 2007), so is our understanding when it comes to the effects of physiological and neurological responses on information retrieval, more specifically on web search performance.
Hence, for us to be able to design better search engines, we need to understand both ‘human-computer-interaction’ as well as ‘brain-computer-interaction’ processes, such that the two not be treated separately.
Keywords: affective information retrieval, affective search, neuro-information science, web search performance, affective information behavior, EEG in information retrieval, emotional design, brain computer interaction