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標題: | 從論文特徵與論文另類使用行為探討另類計量次數在學術評鑑之應用 Exploring the applicability of altmetric counts in research evaluation based upon the characteristic of papers and the alternative usage behaviors |
作者: | 劉杰 Chieh Liu |
指導教授: | 黃慕萱 Mu-Hsuan Huang |
關鍵字: | 網路平台,另類計量次數,被引次數,論文特徵,論文另類使用行為,學術評鑑, online platforms,altmetric counts,citations,the characteristics of papers,alternative usage behaviors,research evaluation, |
出版年 : | 2023 |
學位: | 博士 |
摘要: | 當各種網路平台成為學術傳播的重要途徑之一,許多學者開始討論透過另類計量次數評鑑學術論文的可能性,或許可以藉此觀察論文在學術社群之外的擴散程度。然而網路平台具有多樣化特性,另類計量也尚無一致性標準,在充滿不確定性之下,造成另類計量次數在應用上的困難以及對其有效性的質疑。有鑒於此,本研究以十三種不同網路平台為對象,透過計量與內容分析並行之綜合方法,先比較不同學術領域論文在各種網路平台之另類計量次數差異及其對高被引次數論文的預測能力,再探討各種論文特徵對於另類計量次數之影響,接續分析形成另類計量次數的各種論文另類使用行為,並據此就不同類型的另類計量次數進行討論,最後綜合相關分析結果探究另類計量次數於學術評鑑之應用。
研究結果顯示,不同學術領域論文在各種網路平台之另類計量次數確實存在差異,而其中各學術領域論文在Mendeley平台的另類計量次數總和與論文出現率皆明顯優於其他平台,且其另類計量次數對於各學術領域高被引次數論文皆具有顯著正向的預測能力。而就可能影響另類計量次數的論文特徵來看,僅期刊影響力這項特徵,對於論文之另類計量次數具跨學術領域和網路平台的影響力。進一步分析形成另類計量次數的各種論文另類使用行為,共歸納出取得、轉載、提及、描述、要求、表達、評論與引註等八種類型,而其中只有取得和引註行為產生之另類計量次數對於高被引次數論文有顯著正向的預測能力。綜合相關分析結果,可將各種網路平台依據其在學術評鑑上之應用概分為兩種類型:1) 可應用於評估論文學術影響力之網路平台,包括Mendeley、Patent、Policy與Wikipedia;2) 可作為觀察論文在學術社群外資訊傳播效果之網路平台,包括Facebook、News與Twitter;其餘網路平台則較不適合應用於學術評鑑。 基於上述研究結果,欲將另類計量次數應用於學術評鑑時,建議可針對實務上的特定需求,選擇合適網路平台的另類計量次數,應用於相應的情境中,但應設立相關機制排除刻意操作的情形,以提高其參考價值,此為目前將另類計量次數應用於學術評鑑時的較佳作法。 While online platforms have become one of the important ways in scholarly communication, many researchers have explored the possibility of evaluating academic papers through altmetric counts. However, due to its nature of diversity, there is no common standard for altmetric counts. These uncertainties have caused difficulties in the application of altmetric counts and raised doubts as well. Thus, this study is targeted at 13 different online platforms, combining both informetrics and content analysis methods to explore the applicability of altmetric counts in research evaluation through aspects as follows: firstly, to compare the differences in altmetric counts of different academic fields on various online platforms, and the relationship between altmetric counts and citations. Secondly, to discuss the influence of various characteristics of papers on altmetric counts. Thirdly, to classify the alternative usage behaviors and then identify the user engagement of each altmetric count according to the classification. Lastly, to explore the applicability of altmetric counts in research evaluation based on the above analysis. The results show that there are indeed differences in altmetric counts of academic papers on various online platforms across different academic fields, and among them, the total sum of altmetric counts and coverage on Mendeley are both significantly better than other platforms. Besides, the positive predictive values of highly cited papers were found in the altmetric counts of Mendeley in all academic fields. In terms of the characteristics of papers, the impact of journals is the only factor that significantly associates with increased altmetric counts from almost all online platforms. Furthermore, through content analysis, we discovered eight types of alternative usage behaviors with different user engagement, including access, forward, mention, describe, request, express, comment, and refer. Among all, the positive predictive values of highly cited papers were found in the altmetric counts derived from the behaviors of access and refer only. Overall, the online platforms can be roughly divided into two types according to their applicability in research evaluation: 1) Platforms that are more suitable for evaluating the academic influence of papers, including Mendeley, Patent, Policy, and Wikipedia; 2) Platforms that are more suitable for observing the dissemination of papers outside the academic community, including Facebook, News, and Twitter. The other platforms are less suitable for academic evaluation. Based on the above research results, the following suggestions are made. When applying altmetric counts in research evaluation, it is recommended to select the appropriate platforms considering specific practical needs and situations. Still, it is recommended to exclude the altmetric counts derived from the manipulation by certain filtration mechanisms to improve the reference value of the indicators. This might be the current best practice for applying altmetric counts to research evaluation. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/88058 |
DOI: | 10.6342/NTU202300856 |
全文授權: | 同意授權(全球公開) |
顯示於系所單位: | 圖書資訊學系 |
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