Figure 3. Not affiliated ���]�FV����xNU+k�S�v��^hy�4��k���[k��0]���.���g� �͊g]Vp3�0ӽ�.�8-���`�����r�^U ���Ѣv&�IW��j�I�E�C߱�,�Bڱĭ�iDvo���@>t�H0�:�����4h�jU���'k���R7D>���`�Қ�l�w���];��w�%:���T P� �ɼ ¤�:�.h��$���X� }�;���z��^�W]�5Y{��y�VJ��3�6�w�\y���@n�]PlGayp� A#| u4�^~-�3P�/ yh� �zm��2x��\6��Og�Y��e���G͒��qr��Ƚ�#��������$�]��6 ���27J��0�k�6�v��C�\a|���˅�� $�ă! Part of Springer Nature. Icons helping to collect self reported emotional data in a brand of wearable device (Available from: http://www.warriorwomen.co.uk/2013/05/28/jawbone-up-another-geeky-bracelet-review/, Warriorwoman, 2013). Data from social media has even been used to track influenza epidemics (Ginsberg et al., 2009). A badly designed user interface will require users to focus and concentrate too much of their attention, for too long, with information and feedback that compete for their attention—which has brought the concept of calm technology back on the table (Weiser and Brown, 1995; http://www.calmtech.com/). Table 1. Applications may include investigations about online communications and public opinions about policies, trending political topics, such as environmental concerns, or as means for targeted marketing. 14.6). Even the most sophisticated data sources are reflections of behavior, including attack planning, surveillance, theft of tangible assets, data or intellectual property to name a few. 419–423 (2014), Valakunde, N.D., Patwardhan, M.S. Recently, a few of these cases recent revealed how Twitter feeds can affect markets especially when they are volatile and traded on thin liquidity. Wang, G., Sun, J., Ma, J., Xu, K., Gu, J.: Sentiment classification: the contribution of ensemble learning. For now, this data can be collected in two ways. ���P"�Z�м#�=��J�8wz��hY� @�:�lh�:������Zǡ0)���B_G���Z]��v���sK��>m���t�?�w��6�?`#&�a�Peo���Y�&GkG�����v�=cmЇ%h���k $��8��EU�ű��J��=[�B|�� `6���"��F�}' LcFb2��|�(�����pi���$) I\�x~�Ȣ��1���I��1U�ug�T7\���H50� \{�8~ )�`�xQYȞ�Q��\�D|�����9K��2��.7�>����|Ѓ2����E�h�Ɏ@��`�T�eJe��jÐ�T�))�20���о��Dz誮�. Instr. Sci. Int. It usually relies on applying machine learning techniques to classify documents based on a collection of features extracted from the text using other NLP techniques, such as the presence of certain words or the coverage of some topics. Of these tweets only nine also mentioned Cardinal Jorge Mario Bergoglio, who the papal conclave elected and who then became Pope Francis. Recent technological advances, such as brain scans, endocrine systems, and wearable technologies have allowed the collection of vast amounts of biometric as well as emotional data. Calm technology brings back familiarity and ease of use to help us connect to the world and tune into what is occurring around us, without being overwhelmed by the amount of information. There are various packages that provide sentiment analysis functionality, such as the “RSentiment” package of R (Bose and Goswami, 2017) or the “nltk” package of Python (Bird et al., 2017). Ind. 2.1 Sentiment Analysis Using Deep Learning Deep learning has revolutionized the way of solving problems that were previously done with traditional Machine Learning (ML) techniques. 2017. New Comput. ����)�u;���{xw����ǻ���U��/���4LWUs��o�� ]�V�,��# lV�.��^�����骄�9�@���mY��A�� l$N�dz��P�vA��{͍dzκ�F(�ً�̯aWܮ��җ��+u]sM��kE�2��׫��z�$0-��~����¥��v-n�(�.aP���`܉�f�Ս����e����GM�z3���7�Ԯ�ƞ�i��q���!5��,���z!��V�=f^���Ļ4�����Hx΃�[����?��8莃�.�|k�!����-���ułw��=rc8w����V{]ki�H�W5�Z�U���m�$��w-��1����cj�U��ހ��H|3"s)R\[CqҾ���7i���`e FaM��T=��"�����&�D|�����l��_���X6�t�~�Ƀ�����/�ﵬ�� s�" IEEE, Bashri, M.F.A., Kusumaningrum, R.: Sentiment analysis using Latent Dirichlet Allocation and topic polarity wordcloud visualization.

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