User:Moonstar0619/Contact scraping/Bibliography

Bibliography

This is where you will compile the bibliography for your Wikipedia assignment. Please refer to the following resources for help:

Topic: Contact scraping

1.Symbiotic Relationships: Pragmatic Acceptance of Data Scraping

Jeffrey Kenneth Hirschey. 2014. “Symbiotic Relationships: Pragmatic Acceptance of Data Scraping.” Berkeley Technology Law Journal 29: 897-927.

This is a journal article which focuses on the application of data scraping. The article first acknowledges that automated data collection has many positive applications which benefit both data hosts and scrapers. Then the article states that data scraping is sometimes used in the way which violated the right of data host. The article then identifies the legal defenses data hosts can take to protect database from data scraping, including controlling scraping in their TOUs, practicing IP-blocking, and sending cease-and-desist letters to scrapers. At the end, the article points out that it may not be in data hosts’ business interest to simply sue data scrapers, since both hosts and scrapers can benefit from cooperative scraping. The target audience are scholars who are interested in the ethic of data scraping and legal methods to protect database. In terms of reading difficulty, the first part of article, which generally discusses the application of data scraping, is easy to understand; the second part of article, which lists the technological background for data scraping and defensive measures taken by data hosts, has a higher level of reading difficulty since it contains many specific terms such as “Compilation copyright” and “Click-through agreements”. The article is relatively objective since it discusses both sides of application of data scraping, and it concludes that data scraping is neither positive or negative, but it should be used in a cooperative way. The article introduces me to a wide range of legal protection of databases and the relationship between data hosts and data scraper.

2. A Novel Web Scraping Approach Using the Additional Information Obtained From Web Pages

Uzun, E. 2020. “A Novel Web Scraping Approach Using the Additional Information Obtained From Web Pages.” IEEE Access, Access, IEEE 8 : 61726–40.

This is a journal article which focuses on a new approach of data scraping. The article first acknowledges that most of the previous studies on web scraping are about automatically extracting web content by ignoring time efficiency. Then the article introduces a novel approach, which provides time efficiency by employing the string methods and additional information obtained from web pages of a website during a crawling process. At the end, the researchers of the article states that they plan to develop an effective and efficient web scraper that can create datasets automatically for different purposes. The target audience are scholars who are interested in web scraping and the methods to improve the efficiency of data scraping tools. In terms of reading difficulty, the article has a moderate level of difficult for people who are familiar with web scraping and its tools, while it is difficult for others to understand the terms used in the article. The article is relatively biased since it only lists the advantage new approach of data scraping without its disadvantage compared to traditional approach of data scraping tools. The article introduces me to a new method of data scraping that may be helpful in practice.

3. Liability for Data Scraping Prohibitions under the Refusal to Deal Doctrine: An Incremental Step toward More Robust Sherman Act Enforcement.

Drivas, Ioannis. 2019. “Liability for Data Scraping Prohibitions under the Refusal to Deal Doctrine: An Incremental Step toward More Robust Sherman Act Enforcement.” University of Chicago Law Review 86 (7): 1901–40

This is a journal article which focuses on monopolists’ data scraping prohibitions and its implications as well as liability. The article begins by introducing The Sherman Antitrust Act, and then it lists recent data scraping cases with refusal to deal implications. The article argues that monopolists’ ability to restrict data access poses a grave and novel threat to competition. Then the article discusses the liability for data scraping prohibitions as an incremental solution to digital antitrust concerns. A the end, the article concludes that courts should use impose liability whenever data scraping prohibitions would reduce competition. The target audience are scholars who are studying monopolists’ data scraping prohibitions and its liability in Court. The article is relatively biased since it only focuses on the destructive side of monopolists’ data scraping prohibitions without acknowledging the positive side of monopolists’ data scraping prohibitions (protection of users’ data). The article has a relatively high level in terms of reading difficulty, since it contains many cases under The Sherman Antitrust Act and tone of the whole article is relatively academic. The article introduces me to a new concept of deal liability for data scraping prohibitions, and the ways courts can employ their common law process and adapt the Sherman Act to meet new competitive challenges in the digital economy.

4. The Demise of the Cfaa in Data Scraping Cases

Christensen, Jennie E. 2020. “The Demise of the Cfaa in Data Scraping Cases.” Notre Dame Journal of Law, Ethics & Public Policy 34 (2): 529-47.

This is a journal article which focuses on the legal implication of data scraping. The article begins by providing a basic overview of data scraping and its purpose. Then the article discusses a range of topics: methods to address related issues of cybersecurity as part of their corporate legal guidance; ways in which recent courts have addressed the issue of scraping; and the role of the U.S. Computer Fraud and Abuse Act in addressing the same. At the end, the article concludes that the courts will be increasingly likely to consider data public, and the CFAA may be phased out in all cases involving data scraping. The target audience are scholars who are studying CFAA and legal issues related to data scraping. The article is relatively objective since it mainly discusses the legal implication of data scraping such as the history of CFAA instead of giving an opinion from a biased perspective. In terms of reading difficulty, the article has a relatively high level of difficult for people who are not familiar with legal studies since the article contains different acts that data scraping may violate. The article introduces me to a deeper understanding of the legal implication of data scraping as well as the reason that CFAA may eventually be found to be deemed inapplicable.

5. Monitoring e-commerce adoption from online data

Blazquez, Desamparados, Josep Domenech, Jose A. Gil, and Ana Pont. 2019. “Monitoring E-Commerce Adoption from Online Data.” Knowledge and Information Systems: An International Journal 60 (1): 227-45.

This is a journal article which focuses on an intelligent system to automatically monitor the firms’ engagement in e-commerce. The article begins by introducing the context of web scarping and existing big data learning methods. The article then introduces SAME, the intelligent system developed for automatically detecting and monitoring e-commerce availability. The article also describes the way the system has been tested and evaluated. At the end, the researchers of the article states that they plan to improve SAME to increase the level of detail on the provided output. The target audience are scholars who are interested in the methods to monitoring e-commerce adoption or the application of web scarping tools. In terms of reading difficulty, the article has a moderate level of difficult for people who are familiar with web scraping and its tools, while it is difficult for others to understand the terms used in the article. The article is relatively biased since it only highlights the benefit of using intelligent system without acknowledging to limitation of the system. The article introduces me to a new tool to retrieve and analyze data from corporate websites to discover the adoption of e-commerce, which may be helpful in future practice.

6. A primer on theory-driven web scraping: Automatic extraction of big data from the Internet for use in psychological research.

Landers, Richard N., Robert C. Brusso, Katelyn J. Cavanaugh, and Andrew B. Collmus. 2016. “A Primer on Theory-Driven Web Scraping: Automatic Extraction of Big Data from the Internet for Use in Psychological Research.” Psychological Methods 21 (4): 475–92.

7. Scraping the demos. Digitalization, web scraping and the democratic project

Ulbricht, Lena. 2020. “Scraping the demos. Digitalization, web scraping and the democratic project.”Democratization.27 (3): 426-42.

8. Strategies to access web-enabled urban spatial data for socioeconomic research using R functions

Vallone, Andrés, Coro Chasco, and Beatriz Sánchez. 2020. “Strategies to Access Web-Enabled Urban Spatial Data for Socioeconomic Research Using R Functions.” Journal of Geographical Systems: Spatial Theory, Models, Methods, and Data 22 (2): 217-34.

9. Gather-Narrow-Extract: A Framework for Studying Local Policy Variation Using Web-Scraping and Natural Language Processing

Anglin, Kylie L. 2019. “Gather-Narrow-Extract: A Framework for Studying Local Policy Variation Using Web-Scraping and Natural Language Processing.” Journal of Research on Educational Effectiveness 12 (4): 685–706.

10. Automated Data Collection with R: A Practical Guide to Web Scraping and Text Mining.

Selig, Katharina. 2017. “Automated Data Collection with R: A Practical Guide to Web Scraping and Text Mining.” Biometrics 73 (4): 1469-96.

11. Web scraping techniques to collect data on consumer electronics and airfares for Italian HICP compilation.

Polidoro, Federico, Riccardo Giannini, Rosanna Lo Conte, Stefano Mosca, and Francesca Rossetti. 2015. “Web Scraping Techniques to Collect Data on Consumer Electronics and Airfares for Italian HICP Compilation.” Statistical Journal of the IAOS 31 (2): 165–86.

12. A dive into Web Scraper world

Mahto, Deepak Kumar, and Lisha Singh. 2016. “A Dive into Web Scraper World.” 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), Computing for Sustainable Global Development (INDIACom), 2016 3rd International Conference On, 679–93.

13. Developing a Web Scraping Application with Bypass Blocking

Alexey A. Moskalenko, Olga R. Laponina, and Vladimir A. Sukhomlin. 2019. “Developing a Web Scraping Application with Bypass Blocking.” Sovremennye Informacionnye Tehnologii i IT-Obrazovanie 25 (2): 413–30.

14. Increased information retrieval capabilities on e-commerce websites using scraping techniques

Kurniawati, Deborah, and Deny Triawan. 2017. “Increased Information Retrieval Capabilities on E-Commerce Websites Using Scraping Techniques.” 2017 International Conference on Sustainable Information Engineering and Technology (SIET), Sustainable Information Engineering and Technology (SIET), 2017 International Conference On, 206–29.

15. ProCircle: A promotion platform using crowdsourcing and web data scraping technique

Junjoewong, Lalita, Supatsara Sangnapachai, and Thanwadee Sunetnanta. 2018. “ProCircle: A Promotion Platform Using Crowdsourcing and Web Data Scraping Technique.” 2018 Seventh ICT International Student Project Conference (ICT-ISPC), Student Project Conference (ICT-ISPC), 2018 Seventh ICT International, 1–25.

16. Legality and Ethics of Web Scraping.

Krotov, Vlad, and Leiser Silva. 2018. “Legality and Ethics of Web Scraping.” Proceedings of the Americas Conference on Information Systems (AMCIS).

17. Web Scraping: State-of-the-Art and Areas of Application

Diouf, Rabiyatou, Edouard Ngor Sarr, Ousmane Sall, Babiga Birregah, Mamadou Bousso, and Seny Ndiaye Mbaye. 2019. “Web Scraping: State-of-the-Art and Areas of Application.” 2019 IEEE International Conference on Big Data (Big Data), Big Data (Big Data), 2019 IEEE International Conference On, December, 6040–62.

18. Embedding Content or Interring Copyright: Does the Internet Need the “Server Rule”?

Ginsburg, Jane C., and Luke Ali Budiardjo. 2019. “Embedding Content or Interring Copyright: Does the Internet Need the ‘Server Rule’?” Columbia Journal of Law & the Arts 42 (4): 417–77.

19. Increasing online shop revenues with web scraping: a case study for the wine sector

Jorge, Oriol, Adria Pons, Josep Rius, Carla Vintro, Jordi Mateo, and Jordi Vilaplana. 2020. “Increasing Online Shop Revenues with Web Scraping: A Case Study for the Wine Sector.” British Food Journal.

20. Phishing website detection framework through web scraping and data mining

Park, Andrew J., Ruhi Naaz Quadari, and Herbert H. Tsang. 2017. “Phishing Website Detection Framework through Web Scraping and Data Mining.” 2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), Information Technology, Electronics and Mobile Communication Conference (IEMCON), 2017 8th IEEE Annual, October, 660–84.