No abstract

Public transport requires constant feedback to improve and satisfy daily users. Twitter offers monitoring of user messages, discussion and emoticons addressed to official transport provider accounts. This information can be particularly useful in delicate situations such as management of transit operations during the COVID-19 pandemic. The behaviour of Twitter users in Madrid, London and Prague is analysed with the goal of recognising similar patterns and detecting differences in traffic related topics and temporal cycles. Topics in transit tweets were identified using the bag of words approach and pre-processing in R. COVID-19 is a dominant topic for both London and Madrid but a minor one for Prague, where Twitter serves mainly to deliver messages from politicians and stakeholders. COVID-19 interferes with the meaning of other topics, such as overcrowding or staff. Additionally, specific topics were discovered, such as air quality in Victoria Station, London, or racism in Madrid. For all cities, transit-related tweeting activity declines over weekends. However, London shows much less decline than Prague or Madrid. Weekday daily rhythms show major tweeting activity during the morning in all cities but with different start times. The spatial distribution of tweets for the busiest stations shows that the best-balanced tweeting activity is found in Madrid metro stations.

Využívanie on-line sociálnych sietí je stále viac populárne. Často je študovaná reakcia komunikujúcej verejnosti na rôzne témy, obsahová analýza ich príspevkov a ich sentiment. Príspevok sa zaoberá problémom lokalizácie sťahovaných príspevkov zo siete Twitter, kde len časť obsahuje priamo súradnice. Na príklade tweetov k verejnej doprave z Londýna, Madridu a Prahy dokumentuje možnosti geokódovania, možnosti využitia toponým, presnosť lokalizácie, rozdiely medzi polohou získanou geokóidovaním a skutočnou polohou menovaného objektu a diskutuje problémy lokalizácie a možnosti spresnenia.