| Burst of the filter bubble? Effects of personalization on the diversity of Google News M Haim, A Graefe, HB Brosius Digital Journalism 6 (3), 330-343, 2018 | 562 | 2018 |
| Guide to Automated Journalism A Graefe Tow Center for Digital Journalism, Columbia Journalism School, 2016 | 511 | 2016 |
| Towards pervasive computing in health care–A literature review C Orwat, A Graefe, T Faulwasser BMC medical informatics and decision making 8, 1-18, 2008 | 348 | 2008 |
| Methods to elicit forecasts from groups: Delphi and prediction markets compared KC Green, JS Armstrong, A Graefe Foresight: The International Journal of Applied Forecasting 2007 (8), 17-20, 2007 | 341 | 2007 |
| Readers’ perception of computer-generated news: Credibility, expertise, and readability A Graefe, M Haim, B Haarmann, HB Brosius Journalism 19 (5), 595-610, 2018 | 339 | 2018 |
| Comparing face-to-face meetings, nominal groups, Delphi and prediction markets on an estimation task A Graefe, JS Armstrong International journal of forecasting 27 (1), 183-195, 2011 | 280 | 2011 |
| Golden Rule of Forecasting: Be Conservative JS Armstrong, KC Green, A Graefe Journal of Business Research 68 (8), 1717-1731, 2015 | 246 | 2015 |
| Combining forecasts: An application to elections A Graefe, JS Armstrong, RJ Jones Jr, AG Cuzán International Journal of Forecasting 30 (1), 43-54, 2014 | 239* | 2014 |
| Accuracy of Vote Expectation Surveys in Forecasting Elections A Graefe Public Opinion Quarterly 78 (S1), 204-232, 2014 | 142 | 2014 |
| Automated news: Better than expected? M Haim, A Graefe Digital journalism 5 (8), 1044-1059, 2017 | 128 | 2017 |
| Automated journalism: A meta-analysis of readers’ perceptions of human-written in comparison to automated news A Graefe, N Bohlken Media and communication 8 (3), 50-59, 2020 | 119 | 2020 |
| Key performance indicators to benchmark hospital information systems–a Delphi study G Hübner-Bloder, E Ammenwerth Methods of Information in Medicine 48 (06), 508-518, 2009 | 103 | 2009 |
| Predicting elections from the most important issue: A test of the take‐the‐best heuristic A Graefe, JS Armstrong Journal of Behavioral Decision Making 25 (1), 41-48, 2012 | 91 | 2012 |
| Predicting elections from biographical information about candidates: A test of the index method JS Armstrong, A Graefe Journal of Business Research 64 (7), 699-706, 2011 | 88 | 2011 |
| Prediction markets for foresight A Graefe, S Luckner, C Weinhardt Futures 42 (4), 394-404, 2010 | 70 | 2010 |
| Limitations of Ensemble Bayesian Model Averaging for forecasting social science problems A Graefe, H Küchenhoff, V Stierle, B Riedl International Journal of Forecasting 31 (3), 943-951, 2015 | 67 | 2015 |
| Improving forecasts using equally weighted predictors A Graefe Journal of Business Research 68 (8), 1792-1799, 2015 | 63 | 2015 |
| German Election Forecasting: Comparing and Combining Methods for 2013 A Graefe German Politics 24 (2), 195-204, 2015 | 49 | 2015 |
| A recap of the 2016 election forecasts JE Campbell, H Norpoth, AI Abramowitz, MS Lewis-Beck, C Tien, ... PS: Political Science & Politics 50 (2), 331-338, 2017 | 43 | 2017 |
| Adopting pervasive computing for routine use in healthcare C Orwat, A Rashid, C Holtmann, M Wolk, M Scheermesser, H Kosow, ... IEEE Pervasive Computing 9 (2), 64-71, 2010 | 39 | 2010 |
j scott armstrongThe Wharton School, University of PennsylvaniaVerified email at wharton.upenn.edu
