Exploring User Experience of Smartphones in Social Media: A Mixed-Method Analysis
This study aims to analyze and categorize user experience (UX) of smartphones by utilizing social media data (Twitter). Social media (e.g., Facebook, Twitter) can be helpful for observing natural UX through the users' words. It is a potentially valuable source of data that can be used to examin...
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Veröffentlicht in: | International journal of human-computer interaction 2018-10, Vol.34 (10), p.960-969 |
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description | This study aims to analyze and categorize user experience (UX) of smartphones by utilizing social media data (Twitter). Social media (e.g., Facebook, Twitter) can be helpful for observing natural UX through the users' words. It is a potentially valuable source of data that can be used to examine the thoughts of millions of people. To gather UXs of smartphones, mining social media data (Twitter) techniques were used. Collected UXs were categorized according to the product smartness and the relationship between the product smartness and UXs were identified. A total of 19,288 tweets involving the term "smartphone" were collected from 2014.06.01 to 2014.08.31. Among these, a total of 699 tweets were related to UXs of smartphones. In addition, 478 tweets were categorized according to the five dimensions of product smartness (Autonomy, Adaptability, Multi-functionality, Connectivity, and Personalization). Results found that many satisfactory experiences for all dimensions, but there were unsatisfactory experiences associated with the multi-functionality and connectivity. Findings suggest that mining techniques can be used to gather and analyze UX effectively and efficiently. Also, the results of this study can be helpful for understanding user's implicit needs concerning smartphones, and provide valuable insights for developing smartphones. |
doi_str_mv | 10.1080/10447318.2018.1471572 |
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Social media (e.g., Facebook, Twitter) can be helpful for observing natural UX through the users' words. It is a potentially valuable source of data that can be used to examine the thoughts of millions of people. To gather UXs of smartphones, mining social media data (Twitter) techniques were used. Collected UXs were categorized according to the product smartness and the relationship between the product smartness and UXs were identified. A total of 19,288 tweets involving the term "smartphone" were collected from 2014.06.01 to 2014.08.31. Among these, a total of 699 tweets were related to UXs of smartphones. In addition, 478 tweets were categorized according to the five dimensions of product smartness (Autonomy, Adaptability, Multi-functionality, Connectivity, and Personalization). Results found that many satisfactory experiences for all dimensions, but there were unsatisfactory experiences associated with the multi-functionality and connectivity. Findings suggest that mining techniques can be used to gather and analyze UX effectively and efficiently. 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Social media (e.g., Facebook, Twitter) can be helpful for observing natural UX through the users' words. It is a potentially valuable source of data that can be used to examine the thoughts of millions of people. To gather UXs of smartphones, mining social media data (Twitter) techniques were used. Collected UXs were categorized according to the product smartness and the relationship between the product smartness and UXs were identified. A total of 19,288 tweets involving the term "smartphone" were collected from 2014.06.01 to 2014.08.31. Among these, a total of 699 tweets were related to UXs of smartphones. In addition, 478 tweets were categorized according to the five dimensions of product smartness (Autonomy, Adaptability, Multi-functionality, Connectivity, and Personalization). Results found that many satisfactory experiences for all dimensions, but there were unsatisfactory experiences associated with the multi-functionality and connectivity. Findings suggest that mining techniques can be used to gather and analyze UX effectively and efficiently. Also, the results of this study can be helpful for understanding user's implicit needs concerning smartphones, and provide valuable insights for developing smartphones.</description><subject>Autonomy</subject><subject>Data mining</subject><subject>Digital media</subject><subject>Mixed methods research</subject><subject>Smartphones</subject><subject>Social networks</subject><subject>User experience</subject><subject>User interfaces</subject><issn>1044-7318</issn><issn>1532-7590</issn><issn>1044-7318</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp9kE9PAjEQxRujiYh-BJMmnhf7l249SQioCcQY5NyUbisly3Ztlwjf3hLw6mVmXvJmMu8HwD1GA4xK9IgRY4LickBQLpgJzAW5AD3MKSkEl-gyz9lTHE3X4CalDUKIIE574GOyb-sQffMFl8lGmKWN3jbGwuDgYqtj165DYxP0DVwE43UN57by-gmO4NzvbVXMbbcOFRw1uj4kn27BldN1snfn3gfL6eRz_FrM3l_exqNZYSgtu4IxynBF5bByxFKntWGEZy1KQ5ldlXwluHOCSlZyw5gcSp1TCSFL54ZMMNoHD6e7bQzfO5s6tQm7mJ9IiiAhkcz5aHbxk8vEkFK0TrXR51QHhZE60lN_9NSRnjrTy3vPpz3fuBC3-ifEulKdPmRYLurG-KTo_yd-Ac1JdFo</recordid><startdate>20181003</startdate><enddate>20181003</enddate><creator>Rhiu, Ilsun</creator><creator>Yun, Myung Hwan</creator><general>Taylor & Francis</general><general>Lawrence Erlbaum Associates, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>E3H</scope><scope>F2A</scope><scope>JQ2</scope><orcidid>https://orcid.org/0000-0001-8229-7220</orcidid><orcidid>https://orcid.org/0000-0001-8554-3132</orcidid></search><sort><creationdate>20181003</creationdate><title>Exploring User Experience of Smartphones in Social Media: A Mixed-Method Analysis</title><author>Rhiu, Ilsun ; Yun, Myung Hwan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c338t-44341d396df2e3faac425d3978c34eb85b75ff739485c44969a5727798ff64743</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Autonomy</topic><topic>Data mining</topic><topic>Digital media</topic><topic>Mixed methods research</topic><topic>Smartphones</topic><topic>Social networks</topic><topic>User experience</topic><topic>User interfaces</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rhiu, Ilsun</creatorcontrib><creatorcontrib>Yun, Myung Hwan</creatorcontrib><collection>CrossRef</collection><collection>Library & Information Sciences Abstracts (LISA)</collection><collection>Library & Information Science Abstracts (LISA)</collection><collection>ProQuest Computer Science Collection</collection><jtitle>International journal of human-computer interaction</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rhiu, Ilsun</au><au>Yun, Myung Hwan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Exploring User Experience of Smartphones in Social Media: A Mixed-Method Analysis</atitle><jtitle>International journal of human-computer interaction</jtitle><date>2018-10-03</date><risdate>2018</risdate><volume>34</volume><issue>10</issue><spage>960</spage><epage>969</epage><pages>960-969</pages><issn>1044-7318</issn><eissn>1532-7590</eissn><eissn>1044-7318</eissn><abstract>This study aims to analyze and categorize user experience (UX) of smartphones by utilizing social media data (Twitter). Social media (e.g., Facebook, Twitter) can be helpful for observing natural UX through the users' words. It is a potentially valuable source of data that can be used to examine the thoughts of millions of people. To gather UXs of smartphones, mining social media data (Twitter) techniques were used. Collected UXs were categorized according to the product smartness and the relationship between the product smartness and UXs were identified. A total of 19,288 tweets involving the term "smartphone" were collected from 2014.06.01 to 2014.08.31. Among these, a total of 699 tweets were related to UXs of smartphones. In addition, 478 tweets were categorized according to the five dimensions of product smartness (Autonomy, Adaptability, Multi-functionality, Connectivity, and Personalization). Results found that many satisfactory experiences for all dimensions, but there were unsatisfactory experiences associated with the multi-functionality and connectivity. 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subjects | Autonomy Data mining Digital media Mixed methods research Smartphones Social networks User experience User interfaces |
title | Exploring User Experience of Smartphones in Social Media: A Mixed-Method Analysis |
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