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題名 輔助社群媒體打卡研究之分析工具研發
Development of an analysis tool to facilitate check-in research in social media
作者 梁芷瑄
Liang, Chih Hsuan
貢獻者 李蔡彥
Li, Tsai Yen
梁芷瑄
Liang, Chih Hsuan
關鍵詞 社群媒體
臉書
打卡
視覺化
分析
Social media
Facebook
Check-in
Visualization
Analysis
日期 2017
上傳時間 1-Mar-2017 17:13:40 (UTC+8)
摘要 打卡(Check-in)是Facebook平台上使用者經常使用的功能之一。過去關於打卡的研究大多採用質化的方法，而質性研究者在訪談使用者之前，為了解使用者的資料，往往需要手動查看使用者的Facebook塗鴉牆，收集、整理資料，費時費力。另外，使用者在Facebook上的打卡方式具多樣變化，許多的打卡不具有即時性與適地性。為了了解使用者的打卡動機，我們尚需取得使用者在手機上的操作與位置等資訊，方能還原打卡時的情境。為了了解打卡研究者的研究歷程與需求，我們讓質化研究先行，以進行需求分析，再依其開發一個協助研究者的分析工具，收集整理來自Facebook打卡資料與手機Log的資料，透過視覺化與列表的方式呈現，提供研究者能快速、深入分析、探索使用者在Facebook上打卡的行為與動機。本實驗邀請5位受試者扮演打卡研究分析者的角色，透過系統教學讓受試者學習使用系統，最後讓受試者自由探索使用者的資料集，並記錄下探索歷程與發現。實驗的評分結果使用5分量表，有用性向度的平均分數為4.6，受試者認為本系統能協助他們分析使用者的打卡行為與進行後續研究；易用性向度的平均分數為4.1，系統的操作方式對有的受試者需要時間來學習，但大部份受試者仍對本系統的易用性表示同意，證明本系統兼具有用性與易用性。另外，我們也發現受試者在探索過程與探索結果中展現了對此系統的創用性，是在設計者的預期之外，可見本系統的工具本質。
Check-in is one of the functions that users often use on social media systems such as Facebook. In the past, most of the researchers about check-in use qualitative methods. Before interviewing users, qualitative researchers often need to manually check the user`s timeline on Facebook to collect and sort out data, which is time consuming. In addition, the ways of a user`s check-in’s on Facebook are diversified. Many check-in’s do not synchronize in time and place. To understand the motivation of a user in doing check-in’s, we need to collect more data such as the actions and location on user`s mobile phone to restore the context. In order to assess the need of researchers, we use an interdisciplinary approach, in which qualitative research and tool development run in parallel. We develop a visual analysis tool aiming to help qualitative researchers to analysis data. Our tool collects check-in data from Facebook and synchronizes them with the user log on the user’s mobile phone. By visualizing the data in various forms such as bubble chart, timeline, map, and table, we hope to provide researchers with a quick overview of user behavior as well as in-depth studies of specific events. We use a 5-point scale to evaluate the system in our experiment. The average score of usefulness is 4.6, and the subjects think that our tool is very helpful for them to analyze check-in behaviors and the follow-up qualitative study. The average score of ease-of-use is 4.1. Although most of subjects agree that our system is easy to use, some think that practice is necessary to master the system. In addition, some subjects have found creative uses of our system that were not thought of by the designer, which reflects the nature of our tool in data exploration.
參考文獻 [1] 蘇湘棻, “我迷我打卡？台灣K-POP迷妹的打卡實踐,” 國立政治大學, 2016.
[2] J.Frith, “Communicating through location: The understood meaning of the Foursquare check-in,” J. Comput. Commun., vol. 19, no. 4, pp. 890–905, 2014.
[3] Y.Zheng, “Location-Based Social Networks: Users,” in Computing with Spatial Trajectories, Y.Zheng andX.Zhou, Eds.New York, NY: Springer New York, 2011, pp. 243–276.
[4] 吳筱玫, “網上行走： Facebook 使用者之打卡戰術 與地標實踐,” 新聞學研究, vol. 126, pp. 93–131, 2016.
[5] 萬文隆, “深度訪談在質性研究中的應用,” 2004.
[6] D.Yang, D.Zhang, Z.Yu, andZ.Wang, “A sentiment-enhanced personalized location recommendation system,” Proc. 24th ACM Conf. Hypertext Soc. Media, pp. 119–128, 2013.
[7] J. J.-C.Ying, E. H.-C.Lu, W.-C.Lee, T.-C.Weng, andV. S.Tseng, “Mining user similarity from semantic trajectories,” Proc. 2nd ACM SIGSPATIAL Int. Work. Locat. Based Soc. Networks - LBSN ’10, p. 19, 2010.
[8] J.Thatcher, “Living on Fumes: Digital Footprints, Data Fumes, and the Limitations of Spatial Big Data,” Int. J. Commun., vol. 8, p. 19, 2014.
[9] P.Chen, H.-Y.Wu, C.-Y.Hsu, W.-H.Liao, andT.-Y.Li, “Logging and analyzing mobile user behaviors,” Int. Symp. Cyber Behav. Febr. 10-12, 2012, 2012.
[10] S.Bannur andO.Alonso, “Analyzing Temporal Characteristics of Check-in data,” Www, pp. 827–832, 2014.
[11] G.Andrienko, N.Andrienko, andM.Heurich, “An event-based conceptual model for context-aware movement analysis,” Int. J. Geogr. Inf. Sci., vol. 25, no. March 2015, pp. 1347–1370, 2011.
[12] R.Eccles, T.Kapler, R.Harper, andW.Wright, “Stories in GeoTime,” VAST IEEE Symp. Vis. Anal. Sci. Technol. 2007, Proc., no. December 2007, pp. 19–26, 2007.
[13] D. a.Aoyama, J. T. T.Hsiao, A. F.Cárdenas, andR. K.Pon, “TimeLine and visualization of multiple-data sets and the visualization querying challenge,” J. Vis. Lang. Comput., vol. 18, pp. 1–21, 2007.
[14] M.Khan andS.Khan, “Data and information visualization methods, and interactive mechanisms: A survey,” Int. J. Comput. Appl., vol. 34, no. 1, pp. 1–14, 2011.
[15] M. R.Boland, A.Rusanov, Y.So, C.Lopez-Jimenez, L.Busacca, R. C.Steinman, S.Bakken, J. T.Bigger, andC.Weng, “From expert-derived user needs to user-perceived ease of use and usefulness: A two-phase mixed-methods evaluation framework,” J. Biomed. Inform., vol. 52, pp. 141–150, 2014.
[16] A. M.Lund, “Measuring usability with the USE questionnaire,” Usability interface, vol. 8, no. 2, pp. 3–6, 2001.
[17] F. D.Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of,” MIS Q., vol. 13, no. 3, p. 319–340., 1989.
[18] “App Review - App Development - 文件 - 開發人員專用的 Facebook,” Facebook Developers Doc, 2015. [Online]. Available: https://developers.facebook.com/docs/apps/review. [Accessed: 21-Oct-2015].
[19] “Platform Policy - 開發人員專用的 Facebook,” Facebook Developers Doc, 2015. [Online]. Available: https://developers.facebook.com/policy. [Accessed: 21-Oct-2015].
[20] “Test Users for Apps - App Development - 文件 - 開發人員專用的 Facebook,” Facebook Developers Doc, 2015. [Online]. Available: https://developers.facebook.com/docs/apps/test-users. [Accessed: 21-Oct-2015].
[21] D.Griffiths, “Head First Statistics,” in Head First Statistics, O’Reilly Media, Inc., 2008, p. 5.
[22] E.Segel andJ.Heer, “Narrative visualization: Telling stories with data,” IEEE Trans. Vis. Comput. Graph., vol. 16, no. 6, pp. 1139–1148, 2010.
[23] “Getting started with the Facebook SDK for PHP,” Facebook Developers Doc. [Online]. Available: https://developers.facebook.com/docs/php/gettingstarted/4.0.0. [Accessed: 06-Nov-2015].
[24] “HIGHCHARTS ver.4.2.3,” 2016. [Online]. Available: http://www.highcharts.com/.
[25] “Google Maps JavaScript API,” 2016. [Online]. Available: https://developers.google.com/maps/documentation/javascript/tutorial?hl=zh-tw.
[26] “vis.js - Timeline,” 2016. [Online]. Available: http://visjs.org/docs/timeline/.
[27] “Bootstrap Table,” GitHub, 2016. [Online]. Available: https://github.com/wenzhixin/bootstrap-table.
[28] 林孟穎, “媒體多工行為與注意力和工作記憶關係之探索性研究,” 國立中山大學, 2015.
描述 碩士
國立政治大學
資訊科學學系
102753009
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0102753009
資料類型 thesis
dc.contributor.advisor 李蔡彥zh_TW
dc.contributor.advisor Li, Tsai Yenen_US
dc.contributor.author (Authors) 梁芷瑄zh_TW
dc.contributor.author (Authors) Liang, Chih Hsuanen_US
dc.creator (作者) 梁芷瑄zh_TW
dc.creator (作者) Liang, Chih Hsuanen_US
dc.date (日期) 2017en_US
dc.date.accessioned 1-Mar-2017 17:13:40 (UTC+8)-
dc.date.available 1-Mar-2017 17:13:40 (UTC+8)-
dc.date.issued (上傳時間) 1-Mar-2017 17:13:40 (UTC+8)-
dc.identifier (Other Identifiers) G0102753009en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/106879-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊科學學系zh_TW
dc.description (描述) 102753009zh_TW
dc.description.abstract (摘要) 打卡(Check-in)是Facebook平台上使用者經常使用的功能之一。過去關於打卡的研究大多採用質化的方法，而質性研究者在訪談使用者之前，為了解使用者的資料，往往需要手動查看使用者的Facebook塗鴉牆，收集、整理資料，費時費力。另外，使用者在Facebook上的打卡方式具多樣變化，許多的打卡不具有即時性與適地性。為了了解使用者的打卡動機，我們尚需取得使用者在手機上的操作與位置等資訊，方能還原打卡時的情境。為了了解打卡研究者的研究歷程與需求，我們讓質化研究先行，以進行需求分析，再依其開發一個協助研究者的分析工具，收集整理來自Facebook打卡資料與手機Log的資料，透過視覺化與列表的方式呈現，提供研究者能快速、深入分析、探索使用者在Facebook上打卡的行為與動機。本實驗邀請5位受試者扮演打卡研究分析者的角色，透過系統教學讓受試者學習使用系統，最後讓受試者自由探索使用者的資料集，並記錄下探索歷程與發現。實驗的評分結果使用5分量表，有用性向度的平均分數為4.6，受試者認為本系統能協助他們分析使用者的打卡行為與進行後續研究；易用性向度的平均分數為4.1，系統的操作方式對有的受試者需要時間來學習，但大部份受試者仍對本系統的易用性表示同意，證明本系統兼具有用性與易用性。另外，我們也發現受試者在探索過程與探索結果中展現了對此系統的創用性，是在設計者的預期之外，可見本系統的工具本質。zh_TW
dc.description.abstract (摘要) Check-in is one of the functions that users often use on social media systems such as Facebook. In the past, most of the researchers about check-in use qualitative methods. Before interviewing users, qualitative researchers often need to manually check the user`s timeline on Facebook to collect and sort out data, which is time consuming. In addition, the ways of a user`s check-in’s on Facebook are diversified. Many check-in’s do not synchronize in time and place. To understand the motivation of a user in doing check-in’s, we need to collect more data such as the actions and location on user`s mobile phone to restore the context. In order to assess the need of researchers, we use an interdisciplinary approach, in which qualitative research and tool development run in parallel. We develop a visual analysis tool aiming to help qualitative researchers to analysis data. Our tool collects check-in data from Facebook and synchronizes them with the user log on the user’s mobile phone. By visualizing the data in various forms such as bubble chart, timeline, map, and table, we hope to provide researchers with a quick overview of user behavior as well as in-depth studies of specific events. We use a 5-point scale to evaluate the system in our experiment. The average score of usefulness is 4.6, and the subjects think that our tool is very helpful for them to analyze check-in behaviors and the follow-up qualitative study. The average score of ease-of-use is 4.1. Although most of subjects agree that our system is easy to use, some think that practice is necessary to master the system. In addition, some subjects have found creative uses of our system that were not thought of by the designer, which reflects the nature of our tool in data exploration.en_US
dc.description.tableofcontents 第1章 導論 1
1.1 研究動機 1
1.2 研究目標 3
1.3 研究貢獻 4
1.4 本論文之章節結構 5
第2章 相關研究 6
2.1 地點性質分析 6
2.2 相關的打卡質性研究 6
2.3 空間大數據(spatial big data)的資料收集與分析 7
2.4 多資料集(multiple-data set)與視覺化系統 8
2.5 視覺化方式 8
2.5.1 表格 (Table) 9
2.5.2 氣泡圖 (Bubble Chart) 9
2.5.3 時間軸 (Time Line) 9
2.5.4 地圖 (Map) 9
2.6 實驗評估 10
第3章 系統設計理念與架構 11
3.1 系統架構 11
3.2 資料收集與資料來源 12
3.2.1 Facebook打卡資料 14
3.2.2 Android手機Log資料 14
3.3 資料整合 14
3.3.1 整合Facebook打卡資料集與手機Log資料集 15
3.3.2 研究者分類地點類型 15
3.3.3 情境與資料的對應 16
3.3.4 資料視覺化與情境還原 18
3.4 研究者探索方式 23
3.4.1 互動介面設計 23
3.4.2 Drill-Down Story 25
第4章 系統實作 29
4.1 擷取Facebook資料子系統 29
4.1.1 系統定時擷取Facebook資料 29
4.1.2 資料處理 31
4.2 擷取手機Log子系統 35
4.2.1 前景程式操作記錄 35
4.2.2 位置(Location)記錄 36
4.3 人工處理資料 37
4.3.1 研究者分類地點 37
4.3.2 Facebook打卡資料集與手機Log資料集使用者編號對應 38
4.4 視覺化子系統 39
4.4.1 研究者登入頁面 (Login Page) 39
4.4.2 查詢條件(Data Constraint)結構設計 40
4.4.3 Initial Block 42
4.4.4 Visualization Block 43
4.4.5 Table Block 48
4.4.6 探索歷程 (Search Path) 52
4.4.7 Bookmark 53
4.5 個案分析範例 55
4.5.1 補打卡(非即時打卡)情境 56
4.5.2 快速了解使用者的打卡特性 58
4.5.3 深入探索使用者的打卡 60
第5章 實驗設計與結果分析 63
5.1 實驗目標 63
5.2 實驗對象 63
5.3 實驗流程 65
5.3.1. Facebook頁面查看打卡 66
5.3.2. 系統教學與操作 68
5.3.3. 自由探索 71
5.3.4. 問卷與訪談 72
5.4 實驗結果分析與討論 76
5.4.1. 受試者操作時間 77
5.4.2. 有用性評估 78
5.4.3. 創用性評估 85
5.4.4. 易用性評估 88
第6章 結論與未來展望 91
6.1 研究結論 91
6.2 未來發展與改進 92
6.2.1. 探索方式改進 92
6.2.2. 系統輔助判別改進 93
6.2.3. 暫存探索歷程(Search Path)改進 93
6.2.4. 未來應用 93
參考文獻 95
附錄 98
附錄1 實驗同意書 98
附錄2 實驗流程-自由探索：受試者記錄探索發現與歷程記錄表 99
附錄3 實驗訪談結果 100		zh_TW
dc.format.extent 3280155 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0102753009en_US
dc.subject (關鍵詞) 社群媒體zh_TW
dc.subject (關鍵詞) 臉書zh_TW
dc.subject (關鍵詞) 打卡zh_TW
dc.subject (關鍵詞) 視覺化zh_TW
dc.subject (關鍵詞) 分析zh_TW
dc.subject (關鍵詞) Social mediaen_US
dc.subject (關鍵詞) Facebooken_US
dc.subject (關鍵詞) Check-inen_US
dc.subject (關鍵詞) Visualizationen_US
dc.subject (關鍵詞) Analysisen_US
dc.title (題名) 輔助社群媒體打卡研究之分析工具研發zh_TW
dc.title (題名) Development of an analysis tool to facilitate check-in research in social mediaen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) [1] 蘇湘棻, “我迷我打卡？台灣K-POP迷妹的打卡實踐,” 國立政治大學, 2016.
[2] J.Frith, “Communicating through location: The understood meaning of the Foursquare check-in,” J. Comput. Commun., vol. 19, no. 4, pp. 890–905, 2014.
[3] Y.Zheng, “Location-Based Social Networks: Users,” in Computing with Spatial Trajectories, Y.Zheng andX.Zhou, Eds.New York, NY: Springer New York, 2011, pp. 243–276.
[4] 吳筱玫, “網上行走： Facebook 使用者之打卡戰術 與地標實踐,” 新聞學研究, vol. 126, pp. 93–131, 2016.
[5] 萬文隆, “深度訪談在質性研究中的應用,” 2004.
[6] D.Yang, D.Zhang, Z.Yu, andZ.Wang, “A sentiment-enhanced personalized location recommendation system,” Proc. 24th ACM Conf. Hypertext Soc. Media, pp. 119–128, 2013.
[7] J. J.-C.Ying, E. H.-C.Lu, W.-C.Lee, T.-C.Weng, andV. S.Tseng, “Mining user similarity from semantic trajectories,” Proc. 2nd ACM SIGSPATIAL Int. Work. Locat. Based Soc. Networks - LBSN ’10, p. 19, 2010.
[8] J.Thatcher, “Living on Fumes: Digital Footprints, Data Fumes, and the Limitations of Spatial Big Data,” Int. J. Commun., vol. 8, p. 19, 2014.
[9] P.Chen, H.-Y.Wu, C.-Y.Hsu, W.-H.Liao, andT.-Y.Li, “Logging and analyzing mobile user behaviors,” Int. Symp. Cyber Behav. Febr. 10-12, 2012, 2012.
[10] S.Bannur andO.Alonso, “Analyzing Temporal Characteristics of Check-in data,” Www, pp. 827–832, 2014.
[11] G.Andrienko, N.Andrienko, andM.Heurich, “An event-based conceptual model for context-aware movement analysis,” Int. J. Geogr. Inf. Sci., vol. 25, no. March 2015, pp. 1347–1370, 2011.
[12] R.Eccles, T.Kapler, R.Harper, andW.Wright, “Stories in GeoTime,” VAST IEEE Symp. Vis. Anal. Sci. Technol. 2007, Proc., no. December 2007, pp. 19–26, 2007.
[13] D. a.Aoyama, J. T. T.Hsiao, A. F.Cárdenas, andR. K.Pon, “TimeLine and visualization of multiple-data sets and the visualization querying challenge,” J. Vis. Lang. Comput., vol. 18, pp. 1–21, 2007.
[14] M.Khan andS.Khan, “Data and information visualization methods, and interactive mechanisms: A survey,” Int. J. Comput. Appl., vol. 34, no. 1, pp. 1–14, 2011.
[15] M. R.Boland, A.Rusanov, Y.So, C.Lopez-Jimenez, L.Busacca, R. C.Steinman, S.Bakken, J. T.Bigger, andC.Weng, “From expert-derived user needs to user-perceived ease of use and usefulness: A two-phase mixed-methods evaluation framework,” J. Biomed. Inform., vol. 52, pp. 141–150, 2014.
[16] A. M.Lund, “Measuring usability with the USE questionnaire,” Usability interface, vol. 8, no. 2, pp. 3–6, 2001.
[17] F. D.Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of,” MIS Q., vol. 13, no. 3, p. 319–340., 1989.
[18] “App Review - App Development - 文件 - 開發人員專用的 Facebook,” Facebook Developers Doc, 2015. [Online]. Available: https://developers.facebook.com/docs/apps/review. [Accessed: 21-Oct-2015].
[19] “Platform Policy - 開發人員專用的 Facebook,” Facebook Developers Doc, 2015. [Online]. Available: https://developers.facebook.com/policy. [Accessed: 21-Oct-2015].
[20] “Test Users for Apps - App Development - 文件 - 開發人員專用的 Facebook,” Facebook Developers Doc, 2015. [Online]. Available: https://developers.facebook.com/docs/apps/test-users. [Accessed: 21-Oct-2015].
[21] D.Griffiths, “Head First Statistics,” in Head First Statistics, O’Reilly Media, Inc., 2008, p. 5.
[22] E.Segel andJ.Heer, “Narrative visualization: Telling stories with data,” IEEE Trans. Vis. Comput. Graph., vol. 16, no. 6, pp. 1139–1148, 2010.
[23] “Getting started with the Facebook SDK for PHP,” Facebook Developers Doc. [Online]. Available: https://developers.facebook.com/docs/php/gettingstarted/4.0.0. [Accessed: 06-Nov-2015].
[24] “HIGHCHARTS ver.4.2.3,” 2016. [Online]. Available: http://www.highcharts.com/.
[25] “Google Maps JavaScript API,” 2016. [Online]. Available: https://developers.google.com/maps/documentation/javascript/tutorial?hl=zh-tw.
[26] “vis.js - Timeline,” 2016. [Online]. Available: http://visjs.org/docs/timeline/.
[27] “Bootstrap Table,” GitHub, 2016. [Online]. Available: https://github.com/wenzhixin/bootstrap-table.
[28] 林孟穎, “媒體多工行為與注意力和工作記憶關係之探索性研究,” 國立中山大學, 2015.		zh_TW