文章信息

作者： kaiwu

日期：2024年11月14日

点击数：33

• Chinese
• English
• data
• bibliometrics
• R software
• python
• course: tourism research methods
• kaiwu

 

simulated dataset (tourist satisfaction)

1. questionnaire

     http://kaiwu.city/openfiles/tourist_satisfaction_questionnaire_en.docx

    http://kaiwu.city/openfiles/tourist_satisfaction_questionnaire_en.pdf 

No.	variable	variable labels
1	sid	Respondent ID
2	gender	gender
3	byear	Year of birth
4	region	region
5	income	monthly income
6	expense	daily expense
7	type3	Destination type: nature, culture and mix
8	type2	Destination type: sightseeing vs. participation
9	thotel	Types of hotel
10	sat1	satisfaction: scenery
11	sat2	satisfaction: hotel
12	sat3	satisfaction: food
13	sat4	satisfaction: transportation
14	sat5	satisfaction: travel agency
15	sat6	satisfaction: shopping
16	ri1	Importance: amount
17	ri2	Importance: publishing date
18	ri3	Importance: relevance
19	ri4	Importance: positive
20	ri5	Importance: credibility
21	rp1	Performance: amount
22	rp2	Performance: publishing date
23	rp3	Performance: relevance
24	rp4	Performance: positive
25	rp5	Performance: credibility
26	te1	thrill
27	te2	indulgence
28	te3	enjoyment
29	te4	excitement
30	te5	liberaty
31	te6	freedom
32	te7	refreshment
33	te8	revitalization
34	zh1	uncomfortable when there are many people
35	zh2	I dislike interpersonal communication
36	zh3	I’m not good at interpersonal communication
37	zh4	I try to avoid face-to-face communication
38	zh5	Going out is a tiring thing for me.
39	zh6	I try to avoid going out
40	zh7	It’s troublesome for me to go out.
41	latitude	latitude
42	longitude	longitude

 

value labels
Value labels gender
1	male
2	female.
Value labels region
1	Central China
2	East China
3	North China
4	Northeast China
5	Northwest China
6	Southwest China
7	West China.
Value labels type3
1	natural scenery
2	historical scenery
3	mixed scenery.
Value labels type2
1	sightseeing
2	participation.
Value labels thotel
1	budget hotel
2	luxury hotel
3	bed and breakfast
4	apartment hotel.

 

2. dataset

2.1 csv file

general purpose (without variable labels and value labels)

  http://kaiwu.city/openfiles/tourist.csv

    or

2.2 Excel file

    http://kaiwu.city/openfiles/data_tourist_satisfaction_en.xlsx 

    or

2.3 SPSS file

    http://kaiwu.city/openfiles/data_tourist_satisfaction_en.sav

 

 

3. python ipynb file

  http://kaiwu.city/openfiles/tourist_EN2024Nov10.ipynb 

 

 

4.results

     http://kaiwu.city/openfiles/academic_report_SPSS_EN.docx

 

---

 

3.1 frequency Analysis（discrete variables）

https://libguides.library.kent.edu/SPSS/FrequenciesCategorical

https://www.spss-tutorials.com/spss-frequencies-command/ 

https://datatab.net/tutorial/frequency-table

 

3.2 cross-table（discrete variables）

https://libguides.library.kent.edu/SPSS/Crosstabs 

 

3.3 Descriptive analysis（continuous variables）

https://libguides.library.kent.edu/SPSS/Descriptives

https://www.spss-tutorials.com/spss-descriptives-command/

 

3.4 custom table

https://www.ibm.com/docs/en/spss-statistics/saas?topic=statistics-custom-tables

http://kaiwu.city/index.php/spss-custom-table

 

 

4.relationship between two variables

types of variables (level of measurment)

https://statistics.laerd.com/statistical-guides/types-of-variable.php

https://www.thoughtco.com/independent-and-dependent-variable-examples-606828

https://datatab.net/tutorial/level-of-measurement

4.1 chi-square test

https://libguides.library.kent.edu/SPSS/ChiSquare

https://datatab.net/tutorial/chi-square-test

 

4.2 independent sample t-test

https://libguides.library.kent.edu/SPSS/IndependentTTest

https://datatab.net/tutorial/unpaired-t-test

 

4.3 ANOVA

https://libguides.library.kent.edu/SPSS/OneWayANOVA

https://datatab.net/tutorial/anova

 

4.4 correlation

https://libguides.library.kent.edu/SPSS/PearsonCorr 

https://datatab.net/tutorial/correlation

 

4.5 logistic regression

https://www.spss-tutorials.com/logistic-regression/

https://datatab.net/tutorial/logistic-regression

 

5.analysis for scales (measurement)

5.1 reliability analysis

https://www.spss-tutorials.com/cronbachs-alpha-in-spss/

https://www.spss-tutorials.com/spss-split-half-reliability/

https://datatab.net/tutorial/cronbachs-alpha

 

5.2 exploratory factor analysis (EFA) for validity analysis

https://www.spss-tutorials.com/spss-factor-analysis-tutorial/

https://www.spss-tutorials.com/spss-factor-analysis-intermediate-tutorial/

https://www.spss-tutorials.com/apa-reporting-factor-analysis/

https://datatab.net/tutorial/exploratory-factor-analysis

 

6.export result

https://www.spss-tutorials.com/spss-output/

https://www.spss-tutorials.com/spss-apa-format-descriptives-tables/

 

 

文章信息

作者： kaiwu

日期：2024年11月11日

点击数：532

• Chinese
• data
• bibliometrics
• R software
• python
• course: tourism research methods
• kaiwu

 

  http://kaiwu.city/openfiles/tourist_satisfaction_questionnaire_cn.pdf 

1.python基础

python介绍

http://kaiwu.city/index.php/python

python推荐书籍

http://kaiwu.city/index.php/python-book

 

2.python软件的安装

http://kaiwu.city/index.php/python-vscode

http://kaiwu.city/openfiles/python-3.13.0-amd64.exe 

 

 

http://kaiwu.city/openfiles/tourist.zip 

3.使用python控制Excel

    http://kaiwu.city/openfiles/hotel50python.xlsx 

  http://kaiwu.city/openfiles/python_excel50hotel.ipynb 

 

文章信息

作者： kaiwu

日期：2024年11月09日

点击数：376

• Chinese
• artificial intelligence

https://www.ibm.com/cn-zh/topics/generative-ai

生成式 AI(generative artificial inteligence)，有时也称作 gen AI，是一种人工智能 (AI)，能够创建原创内容（例如文本、图像、视频、音频或软件代码）以响应用户的提示或请求。

1. transform 模型

经典论文

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017). Attention Is All You Need (arXiv:1706.03762). arXiv. https://doi.org/10.48550/arXiv.1706.03762

 

视频解读

https://www.bilibili.com/video/BV1gG411a7bw/

 

科技参考解读

https://www.dedao.cn/course/article?id=3bezDG7wBonmJwgeE9JvQkAg5PyO1x

 

 

 

2.国际网站

2.1 chatGPT from openAI

https://chat.openai.com/

 

2.2 gemini from google

https://gemini.google.com/

 

2.3 claude from anthropic

https://www.anthropic.com/claude

 

2.4 llama from meta

https://llama.meta.com/llama3/

 

 

 

3.国内网站

 

3.1 秘塔metaso

https://metaso.cn/

 

3.2 月之暗面kimi

https://kimi.moonshot.cn/

 

3.3 文心一言（baidu.com）

https://yiyan.baidu.com/

 

3.4 通义千问 （阿里云）

https://tongyi.aliyun.com/ 

 

3.5 讯飞星火（科大讯飞公司iflytek）

https://xinghuo.xfyun.cn/desk

 

3.6 元宝AI（腾讯）

https://hunyuan.tencent.com/ 

3.7 豆包AI（字节跳动）

https://www.doubao.com/chat 

 

3.8 音乐创作suno

https://suno.g-mi.cn/#/

 

 

---

 

4.具体练习

4.1 检索问题

https://metaso.cn/

 

检索短语：旅游体验的本真性问题

检索短语：什么是旅游体验中的建构主义本真？请举出5个例子

 

 

4.2 检索代码

https://www.doubao.com/chat 

检索短语：如何用python导入json格式数据

检索短语：如何把导入的数据另存为feather格式

 

4.3 总结文稿

https://www.doubao.com/chat 

 

Wang, N. (1999). Rethinking Authenticity in Tourism Experience. Annals of Tourism Research, 26(2), 349–370. https://doi.org/10.1016/S0160-7383(98)00103-0

 

英文论文全文下载：

http://kaiwu.city/openfiles/rethinking_authenticity1999wang_ning.pdf

 

短语：请用200字总结一下这个文件

短语：请列出小标题，从6个方面总结一下这个文件
短语：请从5个方面比较一下建构主义本真（Constructive authenticity）与存在主义本真（Existential authenticity）的区别

短语：请从5个方面比较一下reality、authenticity、originality这3个词的区别和联系

 

4.4 OCR识别

https://www.doubao.com/chat 

 

 

GAI平台：

 

https://www.doubao.com/chat 

或

KIMI

https://kimi.moonshot.cn/ 

 

短语：请识别为文字，并用表格整理一下

 

 

 

4.5 翻译

https://www.doubao.com/chat 

 

短语：推迟2天，周六下午两点来我办公室讨论一下，请翻译为英文

短语：请提供8个版本

短语：Happiness through vacationing: Just a temporary boost or long-term benefits，请翻译为中文

短语：Although the potentialities of artificial intelligence (AI) are motivating its fast integration in organizations, our knowledge on how to capture organizational value out of these investments is still scarce. Relying on an approach to dynamic capabilities that focuses on the team level, we examine how humans and AI create interactions that engage both agents in productive dialogue for value co-creation. Our analysis is based on a longitudinal case of the development of a recruitment algorithm at a national subsidiary of Santander bank. Our results allow to identify three main sets of human-AI teaming interactions: achieving interoperability, building trust, and producing mutual knowledge gains. We elaborate a set of propositions on how the value of AI is increased when such interactions are created through productive dialogue, opening the scope for further research on the teaming dynamics that turn the collaboration between both agents into a source of value creation for companie. 请翻译为中文

这段话来自论文的摘要：

 

 

 

 

4.6 诗歌

https://www.doubao.com/chat 

 

短语：请依据《水调歌头》词牌，做出一首词，关于大学生春天郊游

短语：请注意押韵，使用安、然，an这种韵脚

 

 

 

4.7 数据分析

https://www.doubao.com/chat 

  http://kaiwu.city/openfiles/tourist.csv

 

短语：请总结一下这个数据集

短语：请提供对性别gender变量进行频数分析的python代码

 

 

4.8 TTS (text to speech)

https://elevenlabs.io/ 

 ----

https://en.wikipedia.org/wiki/Generative_artificial_intelligence 

Generative artificial intelligence (generative AI, GenAI, or GAI) is artificial intelligence capable of generating text, images, videos, or other data using generative models, often in response to prompts. Generative AI models learn the patterns and structure of their input training data and then generate new data that has similar characteristics.

 

4.9 创作歌曲

https://www.doubao.com/chat 

短语：我想创作一首歌曲，用【自定义歌词】，这首歌是【摇滚】音乐风格，传达【兴奋】的情绪，使用【男声】音色。

 

自定义歌词：侠客行（唐，李白）
赵客缦胡缨，吴钩霜雪明。
银鞍照白马，飒沓如流星。
十步杀一人，千里不留行。
事了拂衣去，深藏身与名。
闲过信陵饮，脱剑膝前横。
将炙啖朱亥，持觞劝侯嬴。
三杯吐然诺，五岳倒为轻。
眼花耳热后，意气素霓生。
救赵挥金槌，邯郸先震惊。
千秋二壮士，烜赫大梁城。
纵死侠骨香，不惭世上英。
谁能书阁下，白首太玄经。

 

 

4.10 生成图片

https://www.doubao.com/chat 

 

短语：请生成一张图片，1个女孩早晨在海边跑步，身着红色T恤，扎马尾辫，海里面有小岛，天上有海鸥，可以看到朝霞。

短语：请生成一张图片，漫画风格，场景是酒店的大堂，展现人工智能对酒店的影响，要有员工、顾客、机器人。

 

 

 

 

 

 

---

5.本地（无需联网）运行大语言模型LLaMa

http://kaiwu.city/index.php/ollama

 

 

文章信息

作者： kaiwu

日期：2024年11月06日

点击数：57

• Chinese
• English
• data
• bibliometrics
• R software
• python
• course: tourism research methods
• kaiwu

 

1.introduction to python

about python

http://kaiwu.city/index.php/python

books on  python

http://kaiwu.city/index.php/python-book

 

2.install python

python 3.13 you can download from official website

https://www.python.org/downloads/ 

or

 http://kaiwu.city/openfiles/python-3.13.0-amd64.exe 

 

http://kaiwu.city/index.php/python-vscode

 

3.python and Excel

    http://kaiwu.city/openfiles/hotel50python_EN.xlsx 

  http://kaiwu.city/openfiles/python_excel50hotel_EN.ipynb 

 

import openpyxl as xl; # be sure to modify the folder where the files are stored.  # The names of the folders should not contain non-English characters and spaces. filename ="D:/tdata/hotel50/hotel50python_EN.xlsx" wb1 = xl.load_workbook(filename) ws1 = wb1.worksheets[0] mr = ws1.max_row mc = ws1.max_column # load the workbook from openpyxl import Workbook # create a new workbook wb2 = Workbook() ws2 =  wb2.active # The "i" represents the row number.  # create a workbook for the data from row 2 to row 50 respectively. for i in range (2, mr + 1):     #The name of the new worksheet: Hotel Name     ws2.title = ws1.cell(row = i, column = 3).value           # j is the column number from 1 to 8:id, hotelid,Hotel Name,Rating,City,Address,Opening Year,Number of Rooms          for j in range (1, mc):         #Copy the first row of the source data, which is the header row, and use it as the first row of the new worksheet.         ws2.cell(row = 1, column = j).value = ws1.cell(row = 1, column = j).value                  # Copy the data in the i-th row of the source data and use it as the 2nd row of the new worksheet.         ws2.cell(row = 2, column = j).value = ws1.cell(row = i, column = j).value     # Save the created Excel workbook.     wb2.save("D:/tdata/hotel50/" + ws2.title + ".xlsx")     # Output the result to indicate the work progress, specifically which worksheet has been completed already.     print('save No. %d Excel file。' % (i-1))