EconBase
← All papers

Nowcasting the euro area with social media data

Konstantin Boss, Luigi Longo, Luca Onorante

arXiv 12 Jun 2025 · Econometrics

arXiv:2506.10546 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Using a state-of-the-art large language model, we extract forward-looking and context-sensitive signals related to inflation and unemployment in the euro area from millions of Reddit submissions and comments. We develop daily indicators that incorporate, in addition to posts, the social interaction among users. Our empirical results show consistent gains in out-of-sample nowcasting accuracy relative to daily newspaper sentiment and financial variables, especially in unusual times such as the (post-)COVID-19 period. We conclude that the application of AI tools to the analysis of social media, specifically Reddit, provides useful signals about inflation and unemployment in Europe at daily frequency and constitutes a useful addition to the toolkit available to economic forecasters and nowcasters.

Citation extraction

36
references
49
in-text mentions
36
distinct cited
1
self-citations
7,501
main-text words

appendix boundary found by appendix_command · 74% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Barbaglia, L., Consoli, S., and Manzan, S (2024) Forecasting gdp in europe with textual data0.8947471%
2Granziera, E., Larsen, V. H., Meggiorini, G., and Melosi, L (2025) Speaking of inflation: the influence of fed speeches on expectations0.7375260%
3Breitung, J. and Roling, C (2015) Forecasting inflation rates using daily data: A nonparametric midas approach0.64422100%
4Barigozzi, M. and Lissona, C (2024) Ea-md-qd: Large euro area and euro member countries datasets for macroeconomic research0.5112250%
5Consoli, S., Barbaglia, L., and Manzan, S (2022) Fine-grained, aspect-based sentiment analysis on economic and financial lexicon0.51121100%
6Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.-A.,… (2023) Llama: Open and efficient foundation language models0.40511100%
7Aliaj, T., Ciganovic, M., and Tancioni, M (2023) Nowcasting inflation with lasso-regularized vector autoregressions and mixed frequency data0.40511100%
8Angelico, C., Marcucci, J., Miccoli, M., and Quarta, F (2022) Can we measure inflation expectations using twitter?0.40511100%
9Aprigliano, V., Emiliozzi, S., Guaitoli, G., Luciani, A., Marcucci,… (2023) The power of text-based indicators in forecasting italian economic activity0.40511100%
10Ashwin, J., Kalamara, E., and Saiz, L (2024) Nowcasting euro area gdp with news sentiment: a tale of two crises0.40511100%

Showing the top 10 of 36 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Nowcasting and aggregation: Why small Euro area countries matter0.64422