Mario Callegaro

2.6k total citations · 1 hit paper
51 papers, 1.6k citations indexed

About

Mario Callegaro is a scholar working on Sociology and Political Science, Communication and Computer Science Applications. According to data from OpenAlex, Mario Callegaro has authored 51 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Sociology and Political Science, 6 papers in Communication and 6 papers in Computer Science Applications. Recurrent topics in Mario Callegaro's work include Survey Methodology and Nonresponse (27 papers), Social Media and Politics (6 papers) and Focus Groups and Qualitative Methods (6 papers). Mario Callegaro is often cited by papers focused on Survey Methodology and Nonresponse (27 papers), Social Media and Politics (6 papers) and Focus Groups and Qualitative Methods (6 papers). Mario Callegaro collaborates with scholars based in United States, United Kingdom and Ecuador. Mario Callegaro's co-authors include Charles DiSogra, Vasja Vehovar, Katja Lozar Manfreda, Jon A. Krosnick, Ana Villar, Paul J. Lavrakas, Yongwei Yang, David S. Yeager, Jelke Bethlehem and Charlotte Steeh and has published in prestigious journals such as SHILAP Revista de lepidopterología, Public Opinion Quarterly and Journal of the Royal Statistical Society Series A (Statistics in Society).

In The Last Decade

Mario Callegaro

48 papers receiving 1.4k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Computing Response Metrics for Online Panels

2008 429 citations Mario Callegaro, Charles DiSogra Public Opinion Quarterly profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Mario Callegaro United States	17	926	210	190	172	163	51	1.6k
LinChiat Chang United States	9	946 1.0×	222 1.1×	204 1.1×	248 1.4×	137 0.8×	12	1.9k
D. A. Dillman United States	14	906 1.0×	143 0.7×	197 1.0×	85 0.5×	153 0.9×	17	1.4k
Reg Baker United States	5	598 0.6×	130 0.6×	144 0.8×	108 0.6×	85 0.5×	9	1.1k
Katja Lozar Manfreda Slovenia	13	888 1.0×	192 0.9×	160 0.8×	53 0.3×	244 1.5×	22	1.9k
Annelies G. Blom Germany	19	841 0.9×	122 0.6×	276 1.5×	133 0.8×	274 1.7×	62	1.6k
Geert Loosveldt Belgium	24	1.3k 1.4×	133 0.6×	267 1.4×	138 0.8×	152 0.9×	117	1.7k
Joseph W. Sakshaug Germany	19	829 0.9×	70 0.3×	293 1.5×	76 0.4×	237 1.5×	95	1.6k
Andy Peytchev United States	19	833 0.9×	71 0.3×	286 1.5×	35 0.2×	157 1.0×	40	1.2k
Vera Toepoel Netherlands	23	885 1.0×	126 0.6×	107 0.6×	22 0.1×	145 0.9×	57	1.5k
Sally Thomas United Kingdom	26	510 0.6×	54 0.3×	99 0.5×	194 1.1×	362 2.2×	136	4.6k

Countries citing papers authored by Mario Callegaro

Since Specialization

Citations

This map shows the geographic impact of Mario Callegaro's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mario Callegaro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mario Callegaro more than expected).

Fields of papers citing papers by Mario Callegaro

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mario Callegaro. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mario Callegaro. The network helps show where Mario Callegaro may publish in the future.

Co-authorship network of co-authors of Mario Callegaro

This figure shows the co-authorship network connecting the top 25 collaborators of Mario Callegaro. A scholar is included among the top collaborators of Mario Callegaro based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mario Callegaro. Mario Callegaro is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Callegaro, Mario, et al.. (2019). “Big Data Meets Survey Science”. Social Science Computer Review. 39(4). 484–488. 8 indexed citations

Callegaro, Mario, et al.. (2017). ESOMAR/GRBN Guideline on Mobile Research. 1 indexed citations

Callegaro, Mario, et al.. (2015). Panel Conditioning and Attrition in the AP-Yahoo! News Election Panel Study. 9 indexed citations

Corbetta, Piergiorgio & Mario Callegaro. (2014). Sui sondaggi politici in Italia. il Mulino. 827–838. 1 indexed citations

Calderwood, Lisa, et al.. (2014). Web Surveys for the General Population: How, why and when?. 5 indexed citations

Murphy, Joe, Michael Link, Casey Langer Tesfaye, et al.. (2014). Social Media in Public Opinion Research: Executive Summary of the Aapor Task Force on Emerging Technologies in Public Opinion Research. Public Opinion Quarterly. 78(4). 788–794. 101 indexed citations

Callegaro, Mario, Ana Villar, David S. Yeager, & Jon A. Krosnick. (2014). A critical review of studies investigating the quality of data obtained with online panels based on probability and nonprobability samples¹. City Research Online (City University London). 23–53. 79 indexed citations

Link, Michael, Joe Murphy, Michael F. Schober, et al.. (2014). Mobile technologies for conducting, augmenting and potentially replacing surveys. 7 indexed citations

Murphy, Joe, Michael Link, Casey Langer Tesfaye, et al.. (2014). Social media in public opinion research: Report of the AAPOR task force on emerging technologies in public opinion research. 31 indexed citations

10.

Callegaro, Mario. (2013). Survey Practice Book List 2013. Survey Practice. 6(1). 1–5.

11.

Villar, Ana, Mario Callegaro, & Yongwei Yang. (2013). Where Am I? A Meta-Analysis of Experiments on the Effects of Progress Indicators for Web Surveys. Social Science Computer Review. 31(6). 744–762. 37 indexed citations

12.

Yang, Yongwei, Mario Callegaro, Dennison S. Bhola, & Don A. Dillman. (2010). IVR and web administration in structured interviews utilizing rating scales: exploring the role of motivation as a moderator to mode effects. International Journal of Social Research Methodology. 14(1). 1–15. 7 indexed citations

13.

Callegaro, Mario & Giancarlo Gasperoni. (2009). Accuracy of Pre-Election Polls for the 2006 Italian Parliamentary Election: Too Close to Call. SSRN Electronic Journal.

14.

Zhang, Chan, Mario Callegaro, Melanie Thomas, & Charles DiSogra. (2009). Do We Hear Different Voices?: Investigating the Differences Between Internet and non-Internet Users On Attitudes and Behaviors. 2 indexed citations

15.

Callegaro, Mario. (2008). Seam effects in longitudinal surveys. Journal of Official Statistics. 24(3). 387–409. 13 indexed citations

16.

Callegaro, Mario & Charles DiSogra. (2008). Computing Response Metrics for Online Panels. SSRN Electronic Journal. 1 indexed citations

17.

Callegaro, Mario & Charles DiSogra. (2008). Computing Response Metrics for Online Panels. Public Opinion Quarterly. 72(5). 1008–1032. 429 indexed citations breakdown →

18.

Steeh, Charlotte, Trent D. Buskirk, & Mario Callegaro. (2007). Using Text Messages in U.S. Mobile Phone Surveys. Field Methods. 19(1). 59–75. 33 indexed citations

19.

Callegaro, Mario. (2007). Seam effects changes due to modifications in question wording and data collection strategies: A comparison of conventional questionnaire and event history calendar seam effects in the PSID. Insecta mundi. 4 indexed citations

20.

Leeuw, Edith D. de, et al.. (2007). The Influence of Advance Letters on Response in Telephone Surveys: A Meta-Analysis. Public Opinion Quarterly. 71(3). 413–443. 84 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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